bachelor's program without specializations supporting Major/Minor study

• Czech
• prof. RNDr. Jiří Barnat, Ph.D.

This study programme is recommended to students who intend to get fundamental knowledge in informatics and get acquainted with the general principals of making and using information technology. Besides, the basic orientation in the field students will get enough knowledge and practical training to be able to find employment in the field immediately after graduation. The programme offers some options to aim the profile of the education towards selected basic areas of computer science, such as computer graphics, data processing, information security, networking, artificial intelligence, and computer science.

Graduates may immediately start working on junior IT positions and will be ready to deepen their knowledge according to the needs of their employer. Graduates are also ready to continue their studies in any master degree programme related to informatics or to opt for some other discipline to get interesting interdisciplinary knowledge.

Requirements for successful graduation

• Obtain at least 180 credits overall and pass the final state exam.
• Obtain 10 credits for SBAPR subject and successfully defend Bachelor's Thesis. See more details.
• Fulfil requirements of a single-field study option or Major study option.
• Pass all the compulsory and elective courses of the program, selected study option, and selected focus with the highest possible graduation form.
• Obtain at least two credits from Physical training. See University Sport Centre.

Compulsory subjects of the program

IB000	Mathematical Foundations of Computer Science
IB002	Algorithms and data structures I
IB005	Formal Languages and Automata
IB015	Non-Imperative Programming
IB111	Foundations of Programming
MB151	Linear models
MB152	Differential and Integral Calculus
MB153	Statistics I
MB154	Discrete mathematics
PB006	Principles of Programming Languages and OOP
PB007	Software Engineering I
PB071	Principles of low-level programming
PB151	Computer Systems
PB152	Operating Systems
PB154	Database Systems
PB156	Computer Networks
PV004	UNIX
PV080	Information security and cryptography
VB000	Elements of Style
VB001	English Exam
SBPrip	Revisions for Bachelor State Exam
SOBHA	Defence of Thesis
SZB	State Exam (Bc degree)
English Obtain at least 2 credits by passing subjects of the following list
VB035	English I
VB036	English II
VV064	Academic and Professional Skills in English for IT
Common university background Obtain at least 10 credits by passing subjects of the following list
IV123	Informatics-Driven Future
VB003	Economic Style of Thinking I
VB004	Economic Style of Thinking II
VB005	Panorama of Physics I
VB006	Panorama of Physics II
VB007	Philosophy of Science I
VB008	Philosophy of Science II
VB010	Philosophy of Language and Its Problems I
VB011	Philosophy of Language and Its Problems II
VB023	Folk Music
VB041	The Principles of Legal Reasoning
VB042	Intellectual Property
VV014	Religionistics
VV015	Political Science
VV018	Topics in Religionistics
VV019	Selected chapters in politology
VV024	Interpretation of Texts
VV026	Creative Writing Workshop
VV027	Postmodern culture
VV028	Psychology in Informatics
VV030	Philosophy and Theories of the Mind
VV031	Basics of Fine Art I
VV032	Introduction to History of Fine Art II
VV040	Theater Play
VV063	Computers and Ergonomy
VV065	Selected chapters in the Theory of Mind

Study option: Single-field study of Informatics

Compulsory subjects and other obligations of the study option

Pass all obligatory courses of the program.
IB107	Computability and Complexity
IB031	Introduction to Machine Learning
PB016	Artificial Intelligence I
Programming Pass at least 1 course of the following list
PB161	C++ Programming
PB162	Java
Fulfil the conditions of at least one focus group.

Focus groups

Recommended course of study

Study option: Major

Compulsory subjects and other obligations of the study option

Pass all obligatory courses of the program.

Fulfill conditions of Minor of another study program.

Recommended course of study

Study option: Minor

Compulsory subjects and other obligations of the study option

IB000	Mathematical Foundations of Computer Science
IB110	Introduction to Informatics
IB113	Introduction to Programming and Algorithms
IB114	Introduction to Programming and Algorithms II
PB001	Introduction to Information Technologies
PB007	Software Engineering I
PB153	Operating Systems and their Interfaces
PB156	Computer Networks
PB168	Introduction to DB and IS
PV004	UNIX
PV157	Authentication and Access Control
IV130	Pros and Cons of Intelligent Systems
IV109	Modeling and Simulation
SZB	State Exam (Bc degree)

Recommended course of study

bachelor's program without specializations

• Czech
• doc. RNDr. Eva Hladká, Ph.D.

The focus of the Programming and development bachelor program is design, creation, implementation, and program maintenance technology and in lesser amount also technical equipment of modern computer systems and digitally controlled systems. Graduates of the program will have a fundamental understanding of the whole computer systems life cycle, starting with computer architectures, programming and software engineering, through computer networks and operating systems and ending with the development of embedded systems. This technological view is supported by the necessary mathematical foundations and by an introduction to design principles of secure computer systems. An important feature of the program is the focus on continuous practical verification of attained knowledge, including semestral project and voluntary semester-long internship. The goal of this program is to focus the graduates on the solving the technological (real world) problems.

Graduates are able to immediately work as junior programmers, designers or members of a test team with fundamentals broad enough for following professional and career growth.

Requirements for successful graduation

• Obtain at least 180 credits overall and pass the final state exam.
• Obtain 10 credits for SBAPR subject and successfully defend Bachelor's Thesis. See more details.
• Pass all the compulsory and elective courses of the program with the highest possible graduation form.
• Obtain at least two credits from Physical training. See University Sport Centre.

Compulsory subjects of the program

IB000	Mathematical Foundations of Computer Science
IB002	Algorithms and data structures I
IB015	Non-Imperative Programming
IB109	Design and Implementation of Parallel Systems
IB110	Introduction to Informatics
IB111	Foundations of Programming
PB006	Principles of Programming Languages and OOP
PB007	Software Engineering I
PB071	Principles of low-level programming
PB138	Modern Markup Languages and Their Applications
PB151	Computer Systems
PB152	Operating Systems
PB152cv	Operating Systems - practicals
PB154	Database Systems
PB156	Computer Networks
PB156cv	Computer Networks - practicals
PB175	Project managment and project
PV028	Applied Information Systems
PV080	Information security and cryptography
PV170	Design of Digital Systems
MB141	Linear algebra and discrete mathematics
MB142	Applied math analysis
MB143	Design and analysis of statistical experiments
PV004	UNIX
VB000	Elements of Style
VB001	English Exam
SBPrip	Revisions for Bachelor State Exam
BStaz	Bachelor internship
SOBHA	Defence of Thesis
SZB	State Exam (Bc degree)
Programming 1 Pass at least 1 course of the following list
PB161	C++ Programming
PB162	Java
Programming 2 Pass at least 1 course of the following list
PB173	Domain specific development in C/C++
PV168	Seminar in Java programming
PV178	Introduction to Development in C#/.NET
PV256	Introduction to Development for Android
English Obtain at least 2 credits by passing subjects of the following list
VB035	English I
VB036	English II
VV064	Academic and Professional Skills in English for IT

Recommended course of study

bachelor's program without specializations supporting Major/Minor study

• Czech
• prof. RNDr. Jiří Zlatuška, CSc.

The aim of this bachelor's study program is to equip applicants with the necessary professional knowledge and the necessary minimum of psychological-pedagogical knowledge for successful work in education in the field of informatics. The program is also a program that in combination with a follow-up teaching program at MU, prepares graduates for the teaching profession. The degree is open only in the minor version in cooperation with the degrees of the Faculty of Science of Masaryk University.

The graduate is ready to continue studying in a follow-up teaching program at MU or can work in various training centers with a focus on IT training.

Requirements for successful graduation

• Obtain at least 180 credits overall and pass the final state exam.
• Obtain 10 credits for SBAPR subject and successfully defend Bachelor's Thesis. See more details.
• Pass all the compulsory and elective courses of the selected study option with the highest possible graduation form.

Study option: Minor

Compulsory subjects and other obligations of the study option

IB000	Mathematical Foundations of Computer Science
IB110	Introduction to Informatics
IB113	Introduction to Programming and Algorithms
IB114	Introduction to Programming and Algorithms II
PB151	Computer Systems
PB153	Operating Systems and their Interfaces
PB156	Computer Networks
PV157	Authentication and Access Control
PB007	Software Engineering I
PB168	Introduction to DB and IS
UB001	Assesment of teaching in Informatics
SBPrip	Revisions for Bachelor State Exam
Programming Pass at least 1 course of the following list
PB161	C++ Programming
PB162	Java
PB071	Principles of low-level programming
Application development Pass at least 1 course of the following list
PB069	Desktop Application Development in C#/.NET
PB138	Modern Markup Languages and Their Applications
PV239	Mobile Application Development
Collect at least 70 credits from courses tought at FI with prefixes IB, IB, PB, or PV.

Recommended course of study

bachelor's program without specializations

• Czech
• doc. RNDr. Tomáš Pitner, Ph.D.

The program will meet the growing interest of both high school graduates and already employed jobseekers without formal education in the field who carry out professions where knowledge and skills in cybersecurity.

Graduates will be ready for a professional of system administrators, operators in information security operations center, CSIRT team members, lower- or middle management in cybersecurity; software engineers of security-relevant IT applications and systems, as well as cybersecurity trainers or assistants to cybersecurity managers.

Requirements for successful graduation

• Obtain at least 180 credits overall and pass the final state exam.
• Obtain 10 credits for SBAPR subject and successfully defend Bachelor's Thesis. See more details.
• Pass all the compulsory and elective courses of the program with the highest possible graduation form.
• Obtain at least two credits from Physical training. See University Sport Centre.

Compulsory subjects of the program

MB141	Linear algebra and discrete mathematics
IB000	Mathematical Foundations of Computer Science
IB110	Introduction to Informatics
IB113	Introduction to Programming and Algorithms
IB114	Introduction to Programming and Algorithms II
PB007	Software Engineering I
PB071	Principles of low-level programming
PB151	Computer Systems
PB152	Operating Systems
PB152cv	Operating Systems - practicals
PB156	Computer Networks
PB156cv	Computer Networks - practicals
PB168	Introduction to DB and IS
PV004	UNIX
PV028	Applied Information Systems
PV080	Information security and cryptography
IV130	Pros and Cons of Intelligent Systems
PV157	Authentication and Access Control
PV175	MS Windows Systems Management I
PV276	Seminar on Simulation of Cyber Attacks
Programming Pass at least 1 course of the following list
PB161	C++ Programming
PB162	Java
Cybersecurity Pass at least 1 course of the following list
PV017	Information Technology Security
PV210	Cyber security in an organization
PrF:BI201K	ICT Law I
PrF:BVV03K	Cybercriminality
FSS:BSSb1101	Introduction into Security and Strategic Studies
FSS:BSSb1103	Security Policy of the Czech Republic
FSS:BSSb1152	Cyber Warfare
BStaz	Bachelor internship
VB000	Elements of Style
English Obtain at least 2 credits by passing subjects of the following list
VB035	English I
VB036	English II
VV064	Academic and Professional Skills in English for IT
VB001	English Exam
SBPrip	Revisions for Bachelor State Exam
SOBHA	Defence of Thesis
SZB	State Exam (Bc degree)

Recommended course of study

follow-up master's program (Czech) with specializations

• Czech
• prof. RNDr. Antonín Kučera, Ph.D.

The study of theoretical computer science focuses on a deeper understanding of basic principles underpinning the development of contemporary information technologies, including non-classical computational devices such as neural networks or quantum computers. Together with the active mastering of advanced theoretical as well as practical concepts, a special emphasis is put on the development of abstract thinking. The students gain a deeper understanding of advanced algorithms, principles of modern programming languages, and methods for verification and analysis of computer programs. Further, they understand the basic advantages and limitations of non-classical computational devices. After successfully completing the programme, the students are qualified for a wide variety of positions requiring complex expert skills.

After successfully completing the study programme, the students are qualified for a variety of IT positions including a developer, system architect, or verification engineer. Solid mathematical skills together with deep knowledge of non-trivial algorithms enable the students to find jobs in the financial sector. The acquired knowledge and skills may be well used also in the follow-up Ph.D. programme.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

IA006	Selected topics on automata theory
IA008	Computational Logic
IA012	Complexity
IV003	Algorithms and Data Structures II
IV054	Coding, Cryptography and Cryptographic Protocols
IV111	Probability in Computer Science
MA007	Mathematical Logic
PA152	Efficient Use of Database Systems
PA159	Net-Centric Computing I
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)

Specialization: Algorithms and Computational Models

Specialization Algorithms and Computational Models will familiarize students with problem solving methods, which are computationally demanding on conventional computers. Graduates are also familiar with the principles, benefits and limitations of non-classical computing systems such as neural networks or quantum computers.

Compulsory subjects of the specialization

IV100	Parallel and distributed computations
IA062	Randomized Algorithms and Computations
IA066	Introduction to Quantum Computing
IA077	Advanced Quantum Information Processing
IA082	Physical concepts of quantum information processing
IA101	Algorithmics for Hard Problems
MA017	Geometric Algorithms
MA018	Numerical Methods
PV021	Neural Networks

Recommended course of study

Specialization: Formal Verification and Program Analysis

The specialization Formal verification and analysis of programs focuses on formal methods for modeling, analysis, testing, and verification of computer programs as one of the basic building blocks of software systems development. Students get acquainted with the principles of modern verification tools and master practical skills required for working in teams responsible for ensuring the quality of the software products (quality assurance teams).

Compulsory subjects of the specialization

IA010	Principles of Programming Languages
IA011	Programming Language Semantics
IA072	Seminar on Verification
IA159	Formal Verification Methods
IA168	Algorithmic game theory
IA169	System Verification and Assurance
IV022	Design and verification of algorithms
PA008	Compiler Construction
PV260	Software Quality

Recommended course of study

Specialization: Principles of Programming Languages

Specialization Principles of programming languages provide a deeper insight into the paradigms of modern programming languages and the structure of their compilers. Graduates can choose the optimal programming tools for a given application type and can quickly acquire new programming languages.

Compulsory subjects of the specialization

IA010	Principles of Programming Languages
IA011	Programming Language Semantics
IA014	Advanced Functional Programming
Advanced Types Pass at least 1 course of the following list
IA038	Types and Proofs
IA081	Lambda calculus
IA158	Real Time Systems
IV010	Communication and Parallelism
PA008	Compiler Construction
PA037	Compiler Project

Recommended course of study

follow-up master's program (Czech) with specializations

• Czech
• doc. RNDr. Tomáš Brázdil, Ph.D.

The Artificial Intelligence and Data Processing program prepares students to work in the areas of design and development of intelligent systems and analysis of big data. These areas are currently undergoing very fast development and are becoming increasingly important. The program leads students to a thorough understanding of basic theoretical concepts and methods. During the study students also solve specific case studies to familiarize themselves with the currently used tools and technologies. Students will thus gain experience that will allow them to immediately use the current state of knowledge in practice, as well as solid foundations, which will enable them to continue to independently follow the developments in the field. The program is divided into four specializations that provide deeper knowledge in a chosen direction. Specializations share a common core, where students learn the most important mathematical, algorithmic, and technological aspects of the field. Machine Learning and Artificial Intelligence specialization lead graduates to gain in-depth knowledge of machine learning and artificial intelligence techniques and to gain experience with their practical application. Natural Language Processing specialization prepares graduates to work with natural languages (eg. Czech, English) in written and spoken form from the perspective of computer science. Data Management and Analysis specialization focus on data science, which creates value from big data by collecting, exploring, interpreting, and presenting data from different viewpoints with the goal of so-called business intelligence. Bioinformatics and Systems Biology specialization focuses on computational methods for automated analysis of large biological data and on creating predictive models of biological processes with the goal to better understand complex biological systems.

Due to the dynamic development of the area, the graduates have a wide range of career opportunities, with specific employment positions being created continuously during the course of their studies. Examples of different types of possible positions: positions in applied and basic research, typically concerning extensive data processing, often also in collaboration with experts from other disciplines such as biology or linguistics; positions in companies with an immediate interest in artificial intelligence and data processing (e.g., Seznam, Google) such as Data Scientist and Machine Learning Engineer; positions in companies that have extensive, valuable data (such as banking, telecom operators) or companies focusing on cloud data analysis, e.g., Business Intelligence Analyst or Data Analyst; graduates can also start their own start-up specializing in the use of artificial intelligence methods in a particular area.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

MA012	Statistics II
IV126	Artificial Intelligence II
PA039	Supercomputer Architecture and Intensive Computations
PA152	Efficient Use of Database Systems
PV021	Neural Networks
PV056	Machine Learning and Data Mining
PV211	Introduction to Information Retrieval
PV251	Visualization
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)

Specialization: Bioinformatics and System Biology

Specialization Bioinformatics and System Biology is intended for students who want to acquire, besides the general knowledge of informatics, the latest knowledge in dynamically developing fields at the border of informatics and biology. By selecting this specialization, the student acquires deep knowledge about the processing, storage, and analysis of biological data or the use of formal methods for analysis and prediction of the behavior of biological systems.

Compulsory subjects of the specialization

IV106	Bioinformatics seminar
IV108	Bionformatics II
IV110	Bionformatics project I
IV120	Continuous and Hybrid Systems
PA054	Formal Methods in Systems Biology
PA183	Project in Systems Biology
PB050	Modelling and Prediction in Systems Biology
PB172	Systems Biology Seminar
PV027	Optimization
PV225	Laboratory of Systems Biology
Applications Pass at least 1 course of the following list
PV269	Advanced methods in bioinformatics
PV270	Biocomputing

Recommended course of study

Specialization: Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence specialization leads graduates to gain in-depth knowledge of machine learning and artificial intelligence techniques and to gain experience with their practical application.

Compulsory subjects of the specialization

IV111	Probability in Computer Science
PA153	Natural Language Processing
Logic and Algorithms Pass at least 3 courses of the following list
MA007	Mathematical Logic
PA164	Machine learning and natural language processing
IA008	Computational Logic
PA163	Constraint programming
IA168	Algorithmic game theory
Applications of Machine Learning Pass at least 1 course of the following list
PA167	Scheduling
PA212	Advanced Search Techniques for Large Scale Data Analytics
PA128	Similarity Searching in Multimedia Data
PV254	Recommender Systems
Projects and Laboratory Obtain at least 4 credits by passing subjects of the following list
PA026	Artificial Intelligence Project
PV115	Laboratory of Knowledge Discovery
IV127	Adaptive Learning Seminar
IV125	Formela lab seminar
Optimizations and Numeric Computing Pass at least 1 course of the following list
PV027	Optimization
MA018	Numerical Methods
PřF:M7PNM1	Advanced numerical methods I

Recommended course of study

Specialization: Data Management and Analysis

Data Management and Analysis specialization focuses on data science, which creates value from big data by collecting, exploring, interpreting, and presenting data from different viewpoints with the goal of so called business intelligence.

Compulsory subjects of the specialization

PA017	Software Engineering II
PA195	NoSQL Databases
PA200	Cloud Computing
PA212	Advanced Search Techniques for Large Scale Data Analytics
PA220	Database systems for data analytics
PV062	File Structures
PV065	UNIX -- Programming and System Management I
PV079	Applied Cryptography
Projects and Laboratory Obtain at least 4 credits by passing subjects of the following list
PV253	Seminar of DISA Laboratory
PV115	Laboratory of Knowledge Discovery

Recommended course of study

Specialization: Natural Language Processing

Natural Language Processing specialization prepares graduates to work with natural languages (eg. Czech, English) in written and spoken form from the perspective of computer science.

Compulsory subjects of the specialization

IA161	Advanced Techniques of Natural Language Processing
IV111	Probability in Computer Science
PA153	Natural Language Processing
PA154	Language Modeling
PA156	Dialogue Systems
Math Pass at least 2 courses of the following list
MA007	Mathematical Logic
IA008	Computational Logic
MA010	Graph Theory
MA015	Graph Algorithms
MV008	Algebra I
MA018	Numerical Methods
PřF:M7130	Computational geometry
Natural Language Processing Pass at least 1 course of the following list
PA164	Machine learning and natural language processing
PV061	Introduction to Machine Translation
IV029	Introduction to Transparent Intensional Logic
Seminar or Project Obtain at least 2 credits by passing subjects of the following list
PV173	Natural Language Processing Seminar
PB106	Corpus Linguistic Project I
PA107	Corpus Tools Project

Recommended course of study

follow-up master's program (Czech) with specializations

• Czech
• doc. RNDr. Petr Matula, Ph.D.

The study program Visual Informatics prepares students to work with image information and spatial scene models that involve or touch areas such as computer graphics, image processing, visualization, computer vision, virtual and expanded reality, video processing, pattern recognition, human-computer communication, 3D modeling, animation, graphic design, and machine learning.

The graduate will find application in various fields, such as the development of graphics applications, simulators, computer games, applications for multimedia processing and analysis, visualization of data, virtual and enhanced reality or creation of the professional-level graphic design. For example, a graduate may be an analyst, graphic designer, application programmer, research or development team leader. The acquired theoretical knowledge and practical skills allow them to thoroughly understand the problems solved and will make it possible in practice to use a wide range of modern technologies - from common mobile devices to dedicated systems with high computing power.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

IV003	Algorithms and Data Structures II
MA018	Numerical Methods
MV013	Statistics for Computer Science
PA103	Object-oriented Methods for Design of Information Systems
PA010	Intermediate Computer Graphics
PV021	Neural Networks
PV182	Human Computer Interaction
PV189	Mathematics for Computer Graphics
PV248	Python
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)

Specialization: Computer Graphics and Visualization

Computer Graphics and Visualization specialization offers the latest knowledge of informatics as well as the knowledge from the dynamically progressing area of computer graphics and its development based on interdisciplinary activities and use in other scientific fields. Students will be acquainted with the principles of graphics architectures, mathematical methods used to solve challenging imaging tasks. The studies provide students with a more in-depth knowledge focused on the design and implementation of software applications using advanced computer graphics technologies.

Compulsory subjects of the specialization

MA017	Geometric Algorithms
PA213	Advanced Computer Graphics
PA093	Computational Geometry Project
PA157	Seminar on Computer Graphics Research
PA166	Advanced Methods of Digital Image Processing
PA214	Visualization II
PV160	Laboratory of Human-Computer Interaction
PV227	GPU Rendering
PV251	Visualization

Recommended course of study

Specialization: Image Processing and Analysis

Image Processing and Analysis specialization provides a comprehensive view of getting and processing image information, starting with simple image editing using point transformations or linear filters, and ending with sophisticated tools such as mathematical morphology or deformable models. Graduates will find their place in the development and deployment of imaging systems in a variety of fields, for example in medicine, biology, meteorological and geographic data processing, biometric applications, etc.

Compulsory subjects of the specialization

MA017	Geometric Algorithms
PA093	Computational Geometry Project
PA166	Advanced Methods of Digital Image Processing
PA170	Digital Geometry
PA171	Digital Image Filtering
PA172	Image Acquisition
PA173	Mathematical Morphology
PV187	Seminar of digital image processing
PV197	GPU Programming

Recommended course of study

Specialization: Computer Game Development

Development of Computer Games specialization gives students a comprehensive insight into how to create graphics aspects of contemporary multimedia entertainment software. Students will become acquainted with modern modeling, imaging and animation techniques, not only in the context of classic 2D and 3D imaging but also in the context of virtual or augmented reality.

Compulsory subjects of the specialization

PA213	Advanced Computer Graphics
PA199	Advanced Game Development
PA215	Game Design I
PA216	Game Design II
PA217	Artificial Intelligence for Computer Games
PA218	Internship - Computer Games
PV227	GPU Rendering
PV255	Game Development I
PV266	Game Development II
VV035	3D Character Modeling
VV036	3D Character Modeling II

Recommended course of study

Specialization: Graphic Design

Graphic Design Specialization offers the study of graphic design and related disciplines in cooperation with the Graphic Design and Multimedia Studio (AGD + M). The studio focuses primarily on digital media, which nowadays replaces most of the printed forms. In terms of mastering high-quality graphic design, this is an identical problem, but digital media opens up new opportunities in communicating with the consumer. For these media, concurrent informatic education of students is necessary and is developed in the course of this specialization. Students work on topics such as game making, interactive information graphics, creating interactive media applications, generative programming, animation, video, 3D digital modeling and 3D printing, e-publishing, web-design, font creation, and more.

Compulsory subjects of the specialization

PV067	Typography II
PV083	Graphic Design II
PV085	Type Design II
PV257	Graphic Design and Multimedia Project
PV259	Generative Design Programming
PV268	Digital Design
VV036	3D Character Modeling II
VV051	Animation
VV068	Concept and Intermedia II
Gr.Design I Obtain at least 5 credits by passing subjects of the following list
PV112	Computer Graphics API
PV239	Mobile Application Development
Gr.Design II Obtain at least 9 credits by passing subjects of the following list
PV156	Digital Photography
VV067	Concept and Intermedia I
VV034	Photography II
VV035	3D Character Modeling
VV050	Motion Design
PV110	Základy filmové řeči
PV101	Type Design III
PV251	Visualization
PV097	Visual creativity informatics

Recommended course of study

follow-up master's program (Czech) with specializations

• Czech
• prof. RNDr. Václav Matyáš, M.Sc., Ph.D.

The study program Computer Systems, Communications and Security aims to lead its graduate to an understanding of architectures, principles, design methods and operations of secure computer systems, respecting both hardware and software aspects, including network communications. The graduate will also gain deeper knowledge in of the chose specializations of the programme.

Program graduate will be prepared to design and maintain operations of secure computer systems with respect to both hardware and software aspects, including network communications. Graduate in the specialization Hardware Systems will be prepared to design solutions to practical problems with the use of computer hardware, to creatively adjust hardware systems and to deploy them. Graduate in the specialization Software Systems will be ready to take various roles in the IT departments taking part in the development and operations of information systems and in the use of IT for support of organizations. Graduates of the specialization Information Security will be able to work in organizations developing or providing systems respecting security requirements, but also in advanced management and operations of such systems. Graduate on the specialization Computer Networks and Communications will be able to work as an architect of large networks, manage network operations and related projects, or to work as an expert in applications or security of computer networks.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

IA158	Real Time Systems
IV054	Coding, Cryptography and Cryptographic Protocols
MV013	Statistics for Computer Science
PA191	Advanced Computer Networking
PV079	Applied Cryptography
PV260	Software Quality
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)
Math Pass at least 2 courses of the following list
IV111	Probability in Computer Science
MA007	Mathematical Logic
MA010	Graph Theory
MA015	Graph Algorithms
MA018	Numerical Methods
Theory of Informatics Pass at least 1 course of the following list
IA101	Algorithmics for Hard Problems
IA169	System Verification and Assurance
Hardware Systems Pass at least 1 course of the following list
PA174	Design of Digital Systems II
PA175	Digital Systems Diagnostics II
PA176	Architecture of Digital Systems II
PA190	Digital Signal Processing
PA192	Secure hardware-based system design
PA221	Hardware description languages
PV191	Project from Designing Digital Systems
PV193	Accelerating Algorithms at Circuit Level
PV194	External Environments of Digital Systems
PV198	Onechip Controllers
PV200	Introduction to hardware description languages

Specialization: Hardware Systems

Specialization Hardware Systems provides specific knowledge to work with programmable structures extending into parallel and distributed systems, computer networks and cryptography. Teaching emphasizes the balance of courses providing the necessary theoretical basis and courses focusing on practical skills that are involved in the design, implementation, analysis, testing and operation of embedded systems. An integral part of the study is also working on a project with a small team and oriented towards experimental and prototype solutions to interesting problems associated with the solution of practical problems arising from research and development activities of the faculty.

Compulsory subjects of the specialization

PB170	Seminar on Digital System Design
PB171	Seminar on Digital System Architecture
PA175	Digital Systems Diagnostics II
PA176	Architecture of Digital Systems II
PA190	Digital Signal Processing
PA221	Hardware description languages
PV191	Project from Designing Digital Systems
PV198	Onechip Controllers

Recommended course of study

Specialization: Software Systems

Specialization Software Systems will lead the graduate to knowledge and skills necessary in all stages of development and changes in extensive software systems, especially information systems. Emphasis is set on knowledge necessary at the design and development of systems with on deployed modern software technologies.

Compulsory subjects of the specialization

IV003	Algorithms and Data Structures II
PA017	Software Engineering II
PA039	Supercomputer Architecture and Intensive Computations
PA103	Object-oriented Methods for Design of Information Systems
PA152	Efficient Use of Database Systems
PA160	Net-Centric Computing II
PA165	Enterprise Applications in Java
PV217	Service Oriented Architecture
PV258	Software Requirements Engineering
Programming Obtain at least 3 credits by passing subjects of the following list
PV179	System Development in C#/.NET
PV248	Python
PV249	Development in Ruby

Recommended course of study

Specialization: Information Security

Specialization Information Security focuses on areas of security in computer systems and networks, cryptography and its applications. The aim is to prepare such a graduate who will be able to work in a variety of roles critical to ensure security of ICTs – specific profiling (e.g., toward cryptography, technological aspects or security management) beyond a common basis of field of study is left to the choice of the student.

Compulsory subjects of the specialization

PV181	Laboratory of security and applied cryptography
PV204	Security Technologies
PA197	Secure Network Design
PA193	Secure coding principles and practices
PA018	Advanced Topics in Information Technology Security
PA168	Postgraduate seminar on IT security and cryptography

Recommended course of study

Specialization: Networks and Communication

Computer Networks and Communications specialization focuses on acquiring advanced knowledge of architectures, operation principles, and principles of operation of computer networks. The field is conceived to satisfy both those interested in practically oriented advanced information and knowledge in the field of computer networks and their applications, as well as those interested in deeper acquaintance with the theoretical fundaments of the field and the study of computer networks as a special case of distributed systems. In addition to knowledge of computer networks, the student acquires knowledge of security, principles of working with multimedia data, basic knowledge of parallel systems and necessary theoretical background.

Compulsory subjects of the specialization

PA039	Supercomputer Architecture and Intensive Computations
PA053	Distributed Systems and Middleware
PA151	Advanced Computer Networks
PA160	Net-Centric Computing II
PV169	Communication Systems Basics
PV188	Principles of Multimedia Processing and Transport
PV233	Networks and Routing Protocols
PV234	LAN Switching and Wireless Networks, WAN

Recommended course of study

follow-up master's program (Czech) with specializations

• Czech
• doc. RNDr. Tomáš Pitner, Ph.D.

The study program develops unique competence profile of the student based on the intersection of multiple areas of knowledge that are relevant for managing the development of software systems and services, as well as cybersecurity management. A specific feature is a focus on strategic and operational management related to the targeting, design, implementation, and operation of software systems and services within the context of organizations and different types with a possible focus on their safe operation or IT services. In addition to developing basic theoretical and technological knowledge and practical developmental skills acquired in the bachelor's study, the content of the follow-up study is extended by other dimensions such as theories and practices of team, project and process management, communication, soft skills and knowledge essential to functioning in economic relations - the basics of marketing, law and others, which especially (but not only) concerns the specialization of service development. The cybersecurity study takes into account aspects of overlapping computer data processing outside of tightly defined system perimeters (e.g. impacting on critical infrastructure), thus enabling a specific multidisciplinary overlap of technical, social and legal aspects in this area.

The graduates find employment in companies and organizations of different sizes and orientation, but they also get the motivation and the possibility of basic preparation for their own innovative business. The strong competitive advantage of the program graduates is the ability to solve complex management-related problems of the development of systems and services for which they can use the acquired skills by the study. Their potential is predestined to hold managerial positions, such as the Chief Information Officer (CIO), project manager, and risk manager. Graduates of the cybersecurity management specialization will find application primarily in companies and institutions that need specialists able to work with relevant coordinating institutions and ensure the management of cybersecurity processes. These are positions as a cybersecurity manager and Chief Information Security Officer (CISO).

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

PA017	Software Engineering II
PV206	Communication and Soft Skills
PV079	Applied Cryptography
MV013	Statistics for Computer Science
PA152	Efficient Use of Database Systems
PA179	Project Management
PA180	Interim Project I+II
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)
Management Pass at least 1 course of the following list
PA182	Managing in Reality
PV214	IT Service Management based on ITIL
PV215	Management by Competencies
PV237	Strategy and Leadership
PV271	Risk Management in IT
PV203	IT Services Management
PV274	Data Quality Management Seminar

Specialization: Software Systems Development and Management

Software Systems Development and Managment specialization focuses on software engineering, i.e., to acquire the knowledge and skills needed at all stages of development, management and maintenance of information, and other types of large software systems. The specialization emphasizes the ability to analyse and specify system requirements, system design, and implementation and deployment.

Compulsory subjects of the specialization

IA169	System Verification and Assurance
PA053	Distributed Systems and Middleware
PA103	Object-oriented Methods for Design of Information Systems
PA165	Enterprise Applications in Java
PA197	Secure Network Design
PV028	Applied Information Systems
Programming Pass at least 1 course of the following list
PA036	Database System Project
PV179	System Development in C#/.NET
PV229	Multimedia Similarity Searching in Practice
PV247	Modern Development of User Interfaces
PV248	Python
PV249	Development in Ruby

Recommended course of study

Specialization: Service Development Management

Services Development Management specialization follows the current large shift from the traditional paradigm of IT design to IT as a service and from product-oriented economy to service-oriented one. Problems and tasks in IT are becoming more complex and the knowledge of IT technology is not sufficient for solving them. A multidisciplinary view is the core of this specialization. Students will gain not only sound IT knowledge (programming, databases, computer security, networks, etc.), but also the skills necessary to understand problems in their complexity (marketing, management, finance or law) as well as necessary communication competencies.

Compulsory subjects of the specialization

PA116	Domain Understanding and Modeling
PA194	Introduction to Service Science
PA181	Services - Systems, Modeling and Execution
PV207	Business Process Management
Computer networks Pass at least 1 course of the following list
PA151	Advanced Computer Networks
PA159	Net-Centric Computing I
PA191	Advanced Computer Networking
PA211	Advanced Topics of Cyber Security
PV210	Cyber security in an organization
PV177	Laboratory of Advanced Network Technologies
Economy Pass at least 1 course of the following list
PV028	Applied Information Systems
PV241	Enterprise and Financial Management
Programming Pass at least 1 course of the following list
PA036	Database System Project
PA165	Enterprise Applications in Java
PV179	System Development in C#/.NET
PV229	Multimedia Similarity Searching in Practice
PV247	Modern Development of User Interfaces
PV248	Python
PV249	Development in Ruby
Soft skills Pass at least 1 course of the following list
ESF:MPV_RKMD	Communication and Managerial Skills training
ESF:MPV_COMA	Communication and Managerial Skills Training
ESF:MPP_CEIT	Czech and European Law of Information Technologies
PV236	Time Management and Effectiveness
PV209	Person Centered Communication
IV057	Seminar on Information Society
PV263	Intercultural Management
IV064	Information Society
PA212	Advanced Search Techniques for Large Scale Data Analytics
Marketing Pass at least 1 course of the following list
PV216	Marketing Strategy in Service Business
PV240	Introduction to service marketing

Recommended course of study

Specialization: Cybersecurity Managment

Cybersecurity Management specialization takes into account the aspects of computer data processing beyond the well-defined system perimeters (e.g., critical infrastructure impact), reflected in the area of cybersecurity and allowing a specific multi-disciplinary overlap of both technical and social and legal aspects of cybersecurity.

Compulsory subjects of the specialization

PrF:BVV14K	Theory and Method of ICT Law
IV054	Coding, Cryptography and Cryptographic Protocols
PrF:BI301K	ICT Law II
PA197	Secure Network Design
PV204	Security Technologies
PA018	Advanced Topics in Information Technology Security
PrF:BVV03K	Cybercriminality
IV128	Online Communication from Social Science Perspective
Computer networks Pass at least 1 course of the following list
PA151	Advanced Computer Networks
PA159	Net-Centric Computing I
PA191	Advanced Computer Networking
PA211	Advanced Topics of Cyber Security
PV210	Cyber security in an organization
PV177	Laboratory of Advanced Network Technologies

Recommended course of study

follow-up master's program (Czech) without specializations supporting Major/Minor study

• Czech
• prof. RNDr. Jiří Zlatuška, CSc.

The aim of this program is to prepare graduates with a range of competencies necessary for the teaching profession. They have both knowledge and skills regarding pupil education, classroom management, and addressing specific learning situations and pupils. The knowledge of individual subjects and the didactic competence ensure a high level of knowledge of the given discipline, which is in accordance to the expected requirements of the secondary schools and the ability of the graduates to mediate the knowledge of the given discipline using a wide range of didactic methods. Graduates are also equipped with the skills and abilities to lead pedagogical communication with students, their parents, colleagues and other subjects (social and communication competencies), educate and motivate pupils, manage classes, participate in school activities and solve specific situations associated with teaching pedagogical-psychological competencies). In addition, graduates are equipped with diagnostic and special pedagogical competencies that enable them to recognize the individual educational and other needs of students, to prepare individual plans for students, to work with counseling specialists, and to apply a wide range of support measures within an inclusive approach. In addition to pedagogical abilities, this program intends to prepare graduates also for the position of school information system manager and administrator.

Graduates of this master degree study program will primarily act as teachers of relevant subjects at secondary schools (grammar schools and secondary technical schools) with accordance of the accredited fields and their focus. In the case the IT administration study plan, graduates will be able to operate in positions of IT administrators at secondary schools.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Fulfil requirements of IT Teacher and Administrator study option or Major study option.
• Pass all the compulsory and elective courses of the program, selected study option with the highest possible graduation form.

Compulsory subjects of the program

PA159	Net-Centric Computing I
PV094	PC Hardware
PV175	MS Windows Systems Management I
PV004	UNIX
UA104	Didactics for Informatics I
UA105	Didactics for Informatics II
UA442	Exercises in Practical Education I
UA542	Exercises in Practical Education II
UA642	Exercises in Practical Education III
VV064	Academic and Professional Skills in English for IT
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)
PřF:XS080	Special pedagogy
PřF:XS092	School management
PřF:XS093	Educational activity with gifted learners
PřF:XS100	Teacher and school administration
PřF:XS130	Personality psychology
PřF:XS150	Educational Psychology
PřF:XS170	Technology for didactics
PřF:XS350	Group dynamic workshop

Study option: Teacher of Informatics and IT administrator

Study option The Informatics Teacher and Network Administrator prepares students for professional positioning as a Network Administrator at a secondary school in parallel with the pedagogical training necessary to obtain secondary school approbation in Informatics.

Compulsory subjects and other obligations of the study option

UB001	Assesment of teaching in Informatics
UA742	Exercises in Practical Education IV
UA842	Exercises in Practical Education V
PB071	Principles of low-level programming
PB138	Modern Markup Languages and Their Applications
PřF:XS020	Inspiratorium for teachers
PřF:XS050	School pedagogy
PřF:XS060	General and alternative didactics
PřF:XS140	Foundations of Psychology
PřF:XS090	Initial teacher training
PřF:XS220	Reflective seminar
Collect at least 36 credits from courses taught at FI with prefixes I or P.

Recommended course of study

Study option: Minor

This study option leads students in cooperation with the Faculty of Science of Masaryk University to obtain two secondary school approbations.

Compulsory subjects and other obligations of the study option

PA159	Net-Centric Computing I
PV175	MS Windows Systems Management I
PV094	PC Hardware
UA104	Didactics for Informatics I
UA105	Didactics for Informatics II
UA442	Exercises in Practical Education I
UA542	Exercises in Practical Education II
UA642	Exercises in Practical Education III
SZMGR	State Exam (MSc degree)
Collect at least 22 credits from courses taught at FI with prefixes I or P.

Recommended course of study

follow-up master's program (English) with specializations

• English
• doc. RNDr. Petr Matula, Ph.D.

The study program Visual Informatics prepares students to work with image information and spatial scene models that involve or touch areas such as computer graphics, image processing, visualization, computer vision, virtual and expanded reality, video processing, pattern recognition, human-computer communication, 3D modeling, animation, graphic design, and machine learning.

The graduate will find application in various fields, such as the development of graphics applications, simulators, computer games, applications for multimedia processing and analysis, visualization of data, virtual and enhanced reality or creation of the professional-level graphic design. For example, a graduate may be an analyst, graphic designer, application programmer, research or development team leader. The acquired theoretical knowledge and practical skills allow them to thoroughly understand the problems solved and will make it possible in practice to use a wide range of modern technologies - from common mobile devices to dedicated systems with high computing power.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

IV003	Algorithms and Data Structures II
MA018	Numerical Methods
MV013	Statistics for Computer Science
PA103	Object-oriented Methods for Design of Information Systems
PA010	Intermediate Computer Graphics
PV021	Neural Networks
PV182	Human Computer Interaction
PV189	Mathematics for Computer Graphics
PV248	Python
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)

Specialization: Computer Graphics and Visualization

Computer Graphics and Visualization specialization offers the latest knowledge of informatics as well as the knowledge from the dynamically progressing area of computer graphics and its development based on interdisciplinary activities and use in other scientific fields. Students will be acquainted with the principles of graphics architectures, mathematical methods used to solve challenging imaging tasks. The studies provide students with a more in-depth knowledge focused on the design and implementation of software applications using advanced computer graphics technologies.

Compulsory subjects of the specialization

MA017	Geometric Algorithms
PA213	Advanced Computer Graphics
PA093	Computational Geometry Project
PA157	Seminar on Computer Graphics Research
PA166	Advanced Methods of Digital Image Processing
PA214	Visualization II
PV160	Laboratory of Human-Computer Interaction
PV227	GPU Rendering
PV251	Visualization

Recommended course of study

Specialization: Image Processing and Analysis

Image Processing and Analysis specialization provides a comprehensive view of getting and processing image information, starting with simple image editing using point transformations or linear filters, and ending with sophisticated tools such as mathematical morphology or deformable models. Graduates will find their place in the development and deployment of imaging systems in a variety of fields, for example in medicine, biology, meteorological and geographic data processing, biometric applications, etc.

Compulsory subjects of the specialization

MA017	Geometric Algorithms
PA093	Computational Geometry Project
PA166	Advanced Methods of Digital Image Processing
PA170	Digital Geometry
PA171	Digital Image Filtering
PA172	Image Acquisition
PA173	Mathematical Morphology
PV187	Seminar of digital image processing
PV197	GPU Programming

Recommended course of study

Specialization: Computer Game Development

Development of Computer Games specialization gives students a comprehensive insight into how to create graphics aspects of contemporary multimedia entertainment software. Students will become acquainted with modern modeling, imaging and animation techniques, not only in the context of classic 2D and 3D imaging but also in the context of virtual or augmented reality.

Compulsory subjects of the specialization

PA213	Advanced Computer Graphics
PA199	Advanced Game Development
PA215	Game Design I
PA216	Game Design II
PA217	Artificial Intelligence for Computer Games
PA218	Internship - Computer Games
PV227	GPU Rendering
PV255	Game Development I
PV266	Game Development II
VV035	3D Character Modeling
VV036	3D Character Modeling II

Recommended course of study

follow-up master's program (English) with specializations

• English
• prof. RNDr. Václav Matyáš, M.Sc., Ph.D.

The study program Computer Systems, Communications and Security aims to lead its graduate to an understanding of architectures, principles, design methods and operations of secure computer systems, respecting both hardware and software aspects, including network communications. The graduate will also gain deeper knowledge in of the chose specializations of the programme.

Program graduate will be prepared to design and maintain operations of secure computer systems with respect to both hardware and software aspects, including network communications. Graduate in the specialization Hardware Systems will be prepared to design solutions to practical problems with the use of computer hardware, to creatively adjust hardware systems and to deploy them. Graduate in the specialization Software Systems will be ready to take various roles in the IT departments taking part in the development and operations of information systems and in the use of IT for support of organizations. Graduates of the specialization Information Security will be able to work in organizations developing or providing systems respecting security requirements, but also in advanced management and operations of such systems. Graduate on the specialization Computer Networks and Communications will be able to work as an architect of large networks, manage network operations and related projects, or to work as an expert in applications or security of computer networks.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

IA158	Real Time Systems
IV054	Coding, Cryptography and Cryptographic Protocols
MV013	Statistics for Computer Science
PA191	Advanced Computer Networking
PV079	Applied Cryptography
PV260	Software Quality
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)
Math Pass at least 2 courses of the following list
IV111	Probability in Computer Science
MA007	Mathematical Logic
MA010	Graph Theory
MA015	Graph Algorithms
MA018	Numerical Methods
Theory of Informatics Pass at least 1 course of the following list
IA101	Algorithmics for Hard Problems
IA169	System Verification and Assurance
Hardware Systems Pass at least 1 course of the following list
PA174	Design of Digital Systems II
PA175	Digital Systems Diagnostics II
PA176	Architecture of Digital Systems II
PA190	Digital Signal Processing
PA192	Secure hardware-based system design
PA221	Hardware description languages
PV191	Project from Designing Digital Systems
PV193	Accelerating Algorithms at Circuit Level
PV194	External Environments of Digital Systems
PV198	Onechip Controllers
PV200	Introduction to hardware description languages

Specialization: Hardware Systems

Specialization Hardware Systems provides specific knowledge to work with programmable structures extending into parallel and distributed systems, computer networks and cryptography. Teaching emphasizes the balance of courses providing the necessary theoretical basis and courses focusing on practical skills that are involved in the design, implementation, analysis, testing and operation of embedded systems. An integral part of the study is also working on a project with a small team and oriented towards experimental and prototype solutions to interesting problems associated with the solution of practical problems arising from research and development activities of the faculty.

Compulsory subjects of the specialization

PB170	Seminar on Digital System Design
PB171	Seminar on Digital System Architecture
PA175	Digital Systems Diagnostics II
PA176	Architecture of Digital Systems II
PA190	Digital Signal Processing
PA221	Hardware description languages
PV191	Project from Designing Digital Systems
PV198	Onechip Controllers

Recommended course of study

Specialization: Software Systems

Specialization Software Systems will lead the graduate to knowledge and skills necessary in all stages of development and changes in extensive software systems, especially information systems. Emphasis is set on knowledge necessary at the design and development of systems with on deployed modern software technologies.

Compulsory subjects of the specialization

IV003	Algorithms and Data Structures II
PA017	Software Engineering II
PA039	Supercomputer Architecture and Intensive Computations
PA103	Object-oriented Methods for Design of Information Systems
PA152	Efficient Use of Database Systems
PA160	Net-Centric Computing II
PA165	Enterprise Applications in Java
PV217	Service Oriented Architecture
PV258	Software Requirements Engineering
Programming Obtain at least 3 credits by passing subjects of the following list
PV179	System Development in C#/.NET
PV248	Python
PV249	Development in Ruby

Recommended course of study

Specialization: Information Security

Specialization Information Security focuses on areas of security in computer systems and networks, cryptography and its applications. The aim is to prepare such a graduate who will be able to work in a variety of roles critical to ensure security of ICTs – specific profiling (e.g., toward cryptography, technological aspects or security management) beyond a common basis of field of study is left to the choice of the student.

Compulsory subjects of the specialization

PV181	Laboratory of security and applied cryptography
PV204	Security Technologies
PA197	Secure Network Design
PA193	Secure coding principles and practices
PA018	Advanced Topics in Information Technology Security
PA168	Postgraduate seminar on IT security and cryptography

Recommended course of study

follow-up master's program (English) with specializations

• English
• doc. RNDr. Tomáš Pitner, Ph.D.

The study program develops unique competence profile of the student based on the intersection of multiple areas of knowledge that are relevant for managing the development of software systems and services, as well as cybersecurity management. A specific feature is a focus on strategic and operational management related to the targeting, design, implementation, and operation of software systems and services within the context of organizations and different types with a possible focus on their safe operation or IT services. In addition to developing basic theoretical and technological knowledge and practical developmental skills acquired in the bachelor's study, the content of the follow-up study is extended by other dimensions such as theories and practices of team, project and process management, communication, soft skills and knowledge essential to functioning in economic relations - the basics of marketing, law and others, which especially (but not only) concerns the specialization of service development. The cybersecurity study takes into account aspects of overlapping computer data processing outside of tightly defined system perimeters (e.g. impacting on critical infrastructure), thus enabling a specific multidisciplinary overlap of technical, social and legal aspects in this area.

The graduates find employment in companies and organizations of different sizes and orientation, but they also get the motivation and the possibility of basic preparation for their own innovative business. The strong competitive advantage of the program graduates is the ability to solve complex management-related problems of the development of systems and services for which they can use the acquired skills by the study. Their potential is predestined to hold managerial positions, such as the Chief Information Officer (CIO), project manager, and risk manager. Graduates of the cybersecurity management specialization will find application primarily in companies and institutions that need specialists able to work with relevant coordinating institutions and ensure the management of cybersecurity processes. These are positions as a cybersecurity manager and Chief Information Security Officer (CISO).

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR subject and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form.
• Fulfil requirements of at least one specialization.

Compulsory subjects of the program

PA017	Software Engineering II
PV206	Communication and Soft Skills
PV079	Applied Cryptography
MV013	Statistics for Computer Science
PA152	Efficient Use of Database Systems
PA179	Project Management
PA180	Interim Project I+II
SOBHA	Defence of Thesis
SZMGR	State Exam (MSc degree)
Management Pass at least 1 course of the following list
PA182	Managing in Reality
PV214	IT Service Management based on ITIL
PV215	Management by Competencies
PV237	Strategy and Leadership
PV271	Risk Management in IT
PV203	IT Services Management
PV274	Data Quality Management Seminar

Specialization: Software Systems Development and Management

Software Systems Development and Managment specialization focuses on software engineering, i.e., to acquire the knowledge and skills needed at all stages of development, management and maintenance of information, and other types of large software systems. The specialization emphasizes the ability to analyse and specify system requirements, system design, and implementation and deployment.

Compulsory subjects of the specialization

IA169	System Verification and Assurance
PA053	Distributed Systems and Middleware
PA103	Object-oriented Methods for Design of Information Systems
PA165	Enterprise Applications in Java
PA197	Secure Network Design
PV028	Applied Information Systems
Programming Pass at least 1 course of the following list
PA036	Database System Project
PV179	System Development in C#/.NET
PV229	Multimedia Similarity Searching in Practice
PV247	Modern Development of User Interfaces
PV248	Python
PV249	Development in Ruby

Recommended course of study

Specialization: Service Development Management

Services Development Management specialization follows the current large shift from the traditional paradigm of IT design to IT as a service and from product-oriented economy to service-oriented one. Problems and tasks in IT are becoming more complex and the knowledge of IT technology is not sufficient for solving them. A multidisciplinary view is the core of this specialization. Students will gain not only sound IT knowledge (programming, databases, computer security, networks, etc.), but also the skills necessary to understand problems in their complexity (marketing, management, finance or law) as well as necessary communication competencies.

Compulsory subjects of the specialization

PA116	Domain Understanding and Modeling
PA194	Introduction to Service Science
PA181	Services - Systems, Modeling and Execution
PV207	Business Process Management
Computer networks Pass at least 1 course of the following list
PA151	Advanced Computer Networks
PA159	Net-Centric Computing I
PA191	Advanced Computer Networking
PA211	Advanced Topics of Cyber Security
PV210	Cyber security in an organization
PV177	Laboratory of Advanced Network Technologies
Economy Pass at least 1 course of the following list
PV028	Applied Information Systems
PV241	Enterprise and Financial Management
Programming Pass at least 1 course of the following list
PA036	Database System Project
PA165	Enterprise Applications in Java
PV179	System Development in C#/.NET
PV229	Multimedia Similarity Searching in Practice
PV247	Modern Development of User Interfaces
PV248	Python
PV249	Development in Ruby
Soft skills Pass at least 1 course of the following list
ESF:MPV_RKMD	Communication and Managerial Skills training
ESF:MPV_COMA	Communication and Managerial Skills Training
ESF:MPP_CEIT	Czech and European Law of Information Technologies
PV236	Time Management and Effectiveness
PV209	Person Centered Communication
IV057	Seminar on Information Society
PV263	Intercultural Management
IV064	Information Society
PA212	Advanced Search Techniques for Large Scale Data Analytics
Marketing Pass at least 1 course of the following list
PV216	Marketing Strategy in Service Business
PV240	Introduction to service marketing

Recommended course of study

Specialization: Cybersecurity Managment

Cybersecurity Management specialization takes into account the aspects of computer data processing beyond the well-defined system perimeters (e.g., critical infrastructure impact), reflected in the area of cybersecurity and allowing a specific multi-disciplinary overlap of both technical and social and legal aspects of cybersecurity.

Compulsory subjects of the specialization

BVV14Keng	Theory of Cyber-Law
IV054	Coding, Cryptography and Cryptographic Protocols
PrF:MVV60K	Cybersecurity Law
PA197	Secure Network Design
PV204	Security Technologies
PA018	Advanced Topics in Information Technology Security
PrF:SOC022	European Cyberlaw
IV128	Online Communication from Social Science Perspective
Computer networks Pass at least 1 course of the following list
PA151	Advanced Computer Networks
PA159	Net-Centric Computing I
PA191	Advanced Computer Networking
PA211	Advanced Topics of Cyber Security
PV210	Cyber security in an organization
PV177	Laboratory of Advanced Network Technologies

Recommended course of study

This list has been built on 4. 8. 2020. Some minor changes may appear during the year, for the current and most up-to-date details see IS MU.

MB141 Linear algebra and discrete mathematics

zk 2/2 3 kr., jaro

• doc. RNDr. Martin Čadek, CSc.
• Prerequisities: ! NOW ( MB151 ) && ( ! MB151 || ! MB154 ) && ( ! MB101 || ! MB104 )
  
• Goals: Introduction to linear algebra, analytical geometry and elementary number theory.
• Learning outcomes: At the end of this course, students should be able to: understand basic concepts of linear algebra; apply these concepts to iterated linear processes; solve basic problems in analytical geometry; apply elemntary number theory on kryptography.
• Syllabus: Obsah kurzu Lineární:
  1. Geometry in plane. Complex numbers. 2. Systems of linear equations. Gauss elimination. 3. Operation with matrices. Inverse matrix, determinent. 4. Vector spaces, báses, dimension, coordinates. 5. Linear mappings, eigenvalues and eigenvectors. 6. Linear processes. 7. Afinne geometry. 8. Scalar product, Eukleidian geometry. 9. Linear optimization. 10. Elementry number theory. 11. Congruences. 12. Application in kryptography.

MB142 Applied math analysis

zk 2/2 3 kr., podzim

• doc. Mgr. Petr Hasil, Ph.D. - doc. RNDr. Michal Veselý, Ph.D.
• Prerequisities: ! MB152 && ! NOW ( MB152 ) && ! MB102 && ! MB202
  High school mathematics
• Goals: This is a basic course of mathematical analysis. The content is differential and integral calculus and infinite series. Students will understand practical methods and will be able to apply these methods to concrete problems. The course places more emphasis on examples.
• Learning outcomes: At the end of the course students will be able to:
  work practically with the derivative and (indefinite and definite) integral;
  analyse the behaviour of functions;
  understand the use of infinite number series and power series;
  understand selected applications of the calculus;
  apply the methods of the calculus to concrete problems.
• Syllabus: Continuous functions and limits
  Derivatives of functions with applications
  Indefinite integrals
  Riemann integral and its applications
  Series

MB143 Design and analysis of statistical experiments

zk 2/2 3 kr., jaro

• prof. RNDr. Jan Slovák, DrSc.
• Prerequisities: MB141 || MB142 || MB101 || MB201 || MB102 || MB202
  
• Goals: Introductory course to educate students in descriptive statistics, theory of probability, random values and probabilistic distributions, including the theory of hypothesis testing.
• Learning outcomes: Upon completing this course, students will be able to perform basic computer aided statistical data set analysis in R language, resulting in tables, graphs and numerical characteristics; will understand basic probability concepts; will be able to solve probability tasks related to explained theory (in some cases using statistical software); will be able to generate realizations of selected types random variables using statistical software; has basic knowledge of statistical hypothesis testing, will be able carry out tests in statistical software and interpret the results.
• Syllabus: Introduction to the probability theory.
  Random variables and vectors. Probability distribution and distribution function.
  Discrete and continuous random variables and vectors. Typical distribution laws. Simultaneous and marginal distributions.
  Stochastic independence of random variables and vectors. The sequence of independent trials.
  Quantiles, expectation, variance, covariance, correlation coeficient and their properties.
  Weak law of large number and central limit theorem.
  Data files, empirical characteristics and graphs, numerical characteristics. Descriptive statistics in R language.
  Random sample, point and interval estimators.
  Basics of testing hypothesis. Testing hypothesis in R language.
  Regression analysis in R language.

MB151 Linear models

zk 2/2 3 kr., jaro

• doc. Mgr. Ondřej Klíma, Ph.D.
• Prerequisities: ! MB101 && ! MB201
  
• Goals: Introduction to linear algebra and analytical geometry.
• Learning outcomes: At the end of this course, students should be able to: understand basic concepts of linear algebra; apply these concepts to iterated linear processes; solve basic problems in analytical geometry.
• Syllabus: The course is the first part of the four semester block of Mathematics. In the entire course, the fundamentals of general algebra and number theory, linear algebra, mathematical analysis, numerical methods, combinatorics, as well as probability and statistics are presented. Content of the course Linear models:
  1. Introduction (3 weeks) -- motivating examples, real and complex numbers, roots of real polynomials, matrix multiplication, recurrence relations (interest computation and recurrence in combinatorics), geometry in two dimensions.
  2. Vector spaces (4 weeks) -- systems of linear equalities, matrix calculus (determinant and inverse matrix), vector spaces (formal definition and examples), linear independence, basis, coordinates, scalar product, length of vector, orthogonality, explicit formulas for recurrence relations.
  3. Linear mappings (2 weeks) -- representation of linear mappings, eigenvalues and eigenvectors; linear transformations in three dimensions, iterated linear processes (population models and discrete Markov chains).
  4. Analytical geometry (4 weeks) -- affine and Euclidean spaces (line, plane descriptions, angle, length, volume); systems of linear (in)equalities - linear programming problem; elementary classification of quadrics.

MB152 Differential and Integral Calculus

zk 2/2 3 kr., podzim

• doc. Mgr. Petr Hasil, Ph.D. - doc. RNDr. Michal Veselý, Ph.D.
• Prerequisities: ( ! MB202 && ! MB102 )
  High school mathematics
• Goals: This is a basic course of the mathematical analysis. The content is the differential and integral calculus and the theory of infinite series. Students will understand theoretical and practical methods and will be able to apply these methods to concrete problems. The emphasis on theory and examples is balanced in the course.
• Learning outcomes: At the end of the course students will be able to:
  work both practically and theoretically with the derivative and (indefinite and definite) integral;
  analyse the behaviour of functions of one real variable.
  understand the theory and use of infinite number series and power series;
  understand the selected applications of the calculus;
  apply the methods of the calculus to concrete problems.
• Syllabus: Continuous functions and limits
  Derivative and its applications
  Elementary functions
  Indefinite integral
  Riemann integral and its applications
  Introduction to differential (and integral) calculus of functions of several variables
  Infinite series

MB153 Statistics I

zk 2/2 3 kr., jaro

• doc. Mgr. Jan Koláček, Ph.D.
• Prerequisities: ( MB151 || MB101 || MB201 || MB152 || MB102 || MB202 ) && ( ! MB103 && ! MB203 && ! MV011 )
  Prerequisites: calculus in one and several variables, basics of linear algebra.
• Goals: Introductory course to educate students in descriptive statistics, theory of probability, random values and probabilistic distributions, including the theory of hypothesis testing.
• Learning outcomes: Upon completing this course, students will be able to perform basic computer aided statistical data set analysis in R language, resulting in tables, graphs and numerical characteristics; will understand basic probability concepts; will be able to solve probability tasks related to explained theory (in some cases using statistical software); will be able to generate realizations of selected types random variables using statistical software; has basic knowledge of statistical hypothesis testing, will be able carry out tests in statistical software and interpret the results.
• Syllabus: Introduction to the probability theory.
  Random variables and vectors. Probability distribution and distribution function.
  Discrete and continuous random variables and vectors. Typical distribution laws. Simultaneous and marginal distributions.
  Stochastic independence of random variables and vectors. The sequence of independent trials.
  Quantiles, expectation, variance, covariance, correlation coeficient and their properties.
  Weak law of large number and central limit theorem.
  Data files, empirical characteristics and graphs, numerical characteristics. Descriptive statistics in R language.
  Random sample, point and interval estimators.
  Basics of testing hypothesis. Testing hypothesis in R language.
  Regression analysis in R language.

MB154 Discrete mathematics

zk 2/2 3 kr., podzim

• prof. RNDr. Jan Slovák, DrSc.
• Prerequisities: ! MB104 && ! MB204 && ( MB101 || MB201 || MB151 || MB102 || MB202 || MB152 )
  High school mathematics. Elementary knowledge of algebraic and combinatorial tasks.
• Goals: Tho goal of this course is to introduce the basics of theory of numbers.
• Learning outcomes: At the end of this course, students should be able to: understand and use methods of number theory to solve simple tasks; understand approximately how results of number theory are applied in cryptography: understand basic computational context; model and solve simple combinatorial problems.
• Syllabus: Number theory:
  divisiblity (gcd, extended Euclid algorithm, Bezout); numerics of big numbers (gcd, modular exponential); prime numbers (properties, basic theorems of arithmetics, factorization, prime number testing (Rabin-Miller, Mersenneho prime numbers); congruences (basic properties, small Fermat theorem; Euler theorem; linear congruences; binomial congruences a primitiv roots; discrete logarithm;
  Number theory applications:
  short introduction to asymetric cryptography (RSA, DH, ElGamal, DSA, ECC); basic coding theory (linear and polynomial codes);
  Combinatorics:
  reminder of basics of combinatorics; generalized binomial theorem; combinatorial identities; Catalan numbers; formal power series; (ordinary) generating functions; exponential generating functions; probabilistic generating functions; solving combinatorial problems with the help of generating functions; solving basic reccurences (Fibonacci).

MA002 Calculus

zk 2/2 3 kr., podzim

• Mgr. Peter Šepitka, Ph.D.
• Prerequisities: Basic knowledge from the calculus and multivariable calculus
• Goals: This course extends the basic knowledge from mathematical analysis. It is devoted to the basic study of systems of linear differential equations, line integrals, the theory of complex functions of complex variable, and calculus of variations.
• Learning outcomes: At the end of the course students should be able to: to define and interpret the basic notions used in the fields mentioned above; to formulate relevant mathematical theorems and statements and to explain methods of their proofs; to use effective techniques utilized in these subject areas; to apply acquired pieces of knowledge for the solution of specific problems; to analyse selected problems from the topics of the course.
• Syllabus: Systems of linear differential equations.
  Line integral.
  Analysis in complex domain.
  Calculus of variations.

MA007 Mathematical Logic

zk 2/1 3 kr., podzim

• prof. RNDr. Antonín Kučera, Ph.D.
• Prerequisities: MB005 || MB101 || MB201 || PřF:M1120 || PřF:M1125
  Students should have passed the course MB005 Foundations of mathematics or the course MB101 Mathematics I. A recommended course is MB008 Algebra I.
• Goals: The course covers basic results about propositional and first order logic, including Gödel's completeness and incompleteness theorems.
• Learning outcomes: At the end of this course, students should be able to:
  understand the difference between formal notions and notions defined at a meta-level;
  understand the difference between validity and provability;
  understand the syntax and semantics of first-order logic;
  understand and appreciate the fundamental ideas in the proofs of Gödel's completeness and incompleteness theorems.
• Syllabus: Propositional calculus: propositional formulas, truth, provability, completeness.
  First-order logic: syntax, semantics.
  A deductive system for first-order logic. Provability, correctness.
  Completeness theorem: theories, models, Gödel's completeness theorem
  Basic model theory, Löwenheim-Skolem theorem
  Gödel's incompleteness theorem.

MA009 Algebra II

zk 2/2 3 kr., jaro

• doc. Mgr. Michal Kunc, Ph.D.
• Prerequisities: ( MB008 || MV008 || program ( N - IN )|| program ( N - AP )|| program ( N - SS ))
  
• Goals: After passing the course, students will be able to: use the basic notions of the theory of lattices and universal algebra; define and understand basic properties of lattices and complete lattices; verify simple algebraic statements; apply theoretical results to algorithmic calculations with operations and terms.
• Learning outcomes: After passing the course, students will be able to: use the basic notions of the theory of lattices and universal algebra; define and understand basic properties of lattices and complete lattices; verify simple algebraic statements; apply theoretical results to algorithmic calculations with operations and terms.
• Syllabus: Lattice theory: semilattices, lattices, lattice homomorphisms, modular and distributive lattices, Boolean algebras, complete lattices, fixed point theorems, closure operators, completion of partially ordered sets, Galois connections, algebraic lattices.
  Universal algebra: algebras, subalgebras, homomorphisms, term algebras, congruences, quotient algebras, direct products, subdirect products, identities, varieties, free algebras, presentations, Birkhoff's theorem, completeness theorem for equational logic, algebraic specifications, rewriting systems.

MA010 Graph Theory

zk 2/1 3 kr., podzim

• prof. RNDr. Daniel Kráľ, Ph.D., DSc.
• Prerequisities: ! PřF:M5140 &&! NOW ( PřF:M5140 )
  Discrete mathematics. IB000 (or equivalent from other schools) is recommended.
• Goals: This is a standard introductory course in graph theory, assuming no prior knowledge of graphs. The course aims to present basic graph theory concepts and statements with a particular focus on those relevant in algorithms and computer science in general. Selected advanced graph theory topics will also be covered. Although the content of this course is primarily targeted at computer science students, it should be accessible to all students.
• Learning outcomes: At the end of the course, students shall understand basic concenpts in graph theory; be able to reproduce the proofs of some fundamental statements in graph theory; be able to solve unseen simple graph theory problems; and be ready to apply their knowledge particularly in computer science.
• Syllabus: Basic graph theory notions: graphs, subgraph, graph isomorphism, vertex degree, paths, connected components, directed graphs.
  Trees and the Minimum Spanning Tree problem.
  Vertex and edge connectivity.
  Planar graphs, duality of planar graphs, Euler's formula and its applications.
  Graph coloring, its basic properties and variants, including edge-coloring and list coloring.
  Matchings in graphs and packing problems.
  Computationally hard graph problems.
  Selected advanced topics (to be chosen from): Interval graphs, chordal graphs, graph minors, graph embeddings on surfaces, Ramsey theory.

MA012 Statistics II

zk 2/2 3 kr., podzim

• Mgr. Ondřej Pokora, Ph.D.
• Prerequisities: Prerequisites: calculus, basics of linear algebra, probability and statistics (including basic experience with software R) from course MV011 Statistics I.
• Goals: The course introduces students to advanced methods of mathematical statistics -- explains the algorithms, computational procedures, conditions, interpretation of results and practical use of these methods for the analysis of real datasets in statistical software R. After completing the course, the student will understand the principles of advanced statistical methods (analysis of variance, nonparametric tests, goodness-of-fit tests, correlation analysis, principal component analysis, generalized linear models, regression diagnostics, independence testing), will be able to use them in analyzing real datasets and will be able to interpret the results.
• Learning outcomes: After completing the course the student will be able to:
  - explain the principles and algorithms of advanced methods of mathematical statistics;
  - perform a statistical analysis of the real dataset in the software R;
  - interpret the results obtained by the statistical analysis.
• Syllabus: Analysis of variance (ANOVA): one- and two-factor, with interactions.
  Nonparametric tests: rank tests.
  Goodness-of-fit tests.
  Correlation analysis, correlation coefficients, rank correlation coefficients.
  Regression diagnostics.
  Autocorrelation, multicollinearity.
  Principal component Analysis (PCA).
  Generalized linear models (GLM): logistic regression and use of ROC curve, some other GLM.
  Contingency tables and independence testing.

MA015 Graph Algorithms

zk 2/1 3 kr., podzim

• doc. Mgr. Jan Obdržálek, PhD.
• Prerequisities: MB005 ||( MB101 && MB102 )||( MB201 && MB102 )||( MB101 && MB202 )||( MB201 && MB202 )||( PřF:M1120 )|| PROGRAM ( N - IN )|| PROGRAM ( N - AP )
  Knowledge of basic graph algorithms and datastructures. Specifically, students should already understand the following datastructures and algorithms: Graphs searching: DFS, BFS. Network flows: Ford-Fulkerson. Minimum spanning trees: Boruvka, Jarnik (Prim), Kruskal. Shortest paths: Bellman-Ford, Dijkstra. Datastructures: priority queues, heaps (incl. Fibonacci), disjoint set (union-find)
• Goals: The course introduces graph important algorithms beyond the reach of standard algorithms and data structures courses. Covered algorithms span most of the important application areas of graphs algorithms.
• Learning outcomes: At the end of the course students will under know and understand important graph algorithms beyond the reach of standard algorithms and data structures courses. Covered algorithms span most of the important application areas of graphs algorithms. The students also should be able to choose an algorithm best suited for a given task, modifying it when necessary, and estimate its complexity.
• Syllabus: Minimum Spanning Trees. Quick overview of basic algorithms (Kruskal, Jarník [Prim], Borůvka) and their modifications. Advanced algorithms: Fredman-Tarjan, Gabow et al. Randomized algorithms: Karger-Klein-Tarjan. Arborescenses of directed graphs, Edmond's branching algorithm.
  Flows in Networks. Revision - Ford-Fulkerson. Edmonds-Karp, Dinic's algorithm (and its variants), MPM (three Indians) algorithm. Modifications for restricted networks.
  Minimum Cuts in Undirected Graphs. All pairs flows/cuts: Gomory-Hu trees. Global minimum cut: node identification algorithm (Nagamochi-Ibaraki), random algorithms (Karger, Karger-Stein)
  Matchings in General Graphs. Basic algorithm using augmenting paths. Perfect matchings: Edmond's blossom algorithm. Maximum matchings. Min-cost perfect matching: Hungarian algorithm.
  Dynamic Algorithms for Hard Problems. Dynamic programming on trees and circular-arc graphs. Tree-width; dynamic programming on tree-decompositions.
  Graph Isomorphism. Colour refinement. Individualisation-refinement algorithms. Tractable classes of graphs.

MA017 Geometric Algorithms

zk 2/0 2 kr., podzim

• John Denis Bourke, PhD. - doc. RNDr. Martin Čadek, CSc.
• Prerequisities: Basic course on algorithms, high school geometry.
• Goals: The aim of the course is to introduce the principles of basic algorithms in computational geometry. This course can be followed by the PA093 Computational Geometry Project where the students are implemented selected algorithms in practice.
• Learning outcomes: Students will gain knowledge about state-of-the-art algorithmic methods in this field, along with their complexity and underlying data and searching structures.
• Syllabus: 1. Algorithms for construction of convex hulls in two-dimensional space 2. Line segment intersections 3. Triangulations 4. Linear programming in two-dimensional space 5. Range searching (kd-trees, range trees) 6. Point localization 7. Voronoi diagrams 8. Duality and arrangements 9. Delaunay triangulation 10. Convex hulls in in three-dimensional space

MA018 Numerical Methods

zk 2/2 3 kr., podzim

• Mgr. Jiří Zelinka, Dr.
• Prerequisities: Differential calculus of functions of one and more variables. Basic knoledge of linear algebra-theory of matrices and solving systems of linear equations.
• Goals: This course provides explanation of numerical mathematics as the separate scientific discipline. The emphasis is given to the algorithmization and computer implementation. Examples with graphical outputs help to explain even some difficult parts.
• Learning outcomes: At the end of course students should be able to apply numerical methods for solving practical problems and use these methods in other disciplines.
• Syllabus: 1. Error analysis: absolute and relative error, representation of numbers, error propagation
  2. Iterative methods for solving of nonlinear equations: general iterative method, order of the convergence, Newton method and its modifications
  3. Direct methods for solving systems of linear equations: methods based on Gaussian elimination, methods for special matrices
  4. Iterative methods for solving of systems of linear equations: general construction of iterative methods, Jacobi method, Gauss-Seidel method
  5. Solving of systems of nonlinear equations: Newton method
  6. Interpolation and approximation: polynomial and piece-wise polynomial interpolation, curve approximations, subdivision schemes, least squares method
  7. Numerical differentiation: differentiation schemes
  8. Numerical integration: methods based on interpolation, Monte Carlo integration

MV008 Algebra I

zk 2/2 3 kr., podzim

• doc. Mgr. Ondřej Klíma, Ph.D. - doc. Mgr. Michal Kunc, Ph.D.
• Prerequisities: ( MB005 || MB101 || MB201 ) && ! MB008
  
• Goals: After passing the course, students will be able to: use the basic notions of the theory of monoids, groups and rings; define and understand basic properties of these structures; verify simple algebraic statements; apply theoretical results to algorithmic calculations with numbers, mappings and polynomials.
• Learning outcomes: After passing the course, students will be able to: use the basic notions of the theory of monoids, groups and rings; define and understand basic properties of these structures; verify simple algebraic statements; apply theoretical results to algorithmic calculations with numbers, mappings and polynomials.
• Syllabus: Semigroups: monoids, subsemigroups and submonoids, homomorphisms and isomorphisms, Cayley's representation, transition monoids of automata, direct products of semigroups, invertible elements.
  Groups: basic properties, subgroups, homomorphisms and isomorphisms, cyclic groups, Cayley's representation, direct products of groups, cosets of a subgroup, Lagrange's theorem, normal subgroups, quotient groups.
  Polynomials: polynomials over complex, real, rational and integer numbers, polynomials over residue classes, divisibility, irreducible polynomials, roots, minimal polynomials of numbers.
  Rings: basic properties, subrings, homomorphisms and isomorphisms, direct products of rings, integral domains, fields, fields of fractions, divisibility, polynomials over a field, ideals, quotient rings, field extensions, finite fields.

MV011 Statistics I

zk 2/2 4 kr., jaro

• doc. Mgr. Jan Koláček, Ph.D.
• Prerequisities: Prerequisites: calculus in one and several variables, basics of linear algebra.
• Goals: Upon completing this course, students will be able to perform basic computer aided statistical data set analysis in R language, resulting in tables, graphs and numerical characteristics; will understand basic probability concepts; will be able to solve probability tasks related to explained theory (in some cases using statistical software); will be able to generate realizations of selected types random variables using statistical software; has basic knowledge of statistical hypothesis testing, will be able carry out tests in statistical software and interpret the results.
• Syllabus: Introduction to the probability theory.
  Random variables and vectors. Probability distribution and distribution function.
  Discrete and continuous random variables and vectors. Typical distribution laws. Simultaneous and marginal distributions.
  Stochastic independence of random variables and vectors. The sequence of independent trials.
  Quantiles, expectation, variance, covariance, correlation coeficient and their properties.
  Weak law of large number and central limit theorem.
  Data files, empirical characteristics and graphs, numerical characteristics. Descriptive statistics in R language.
  Random sample, point and interval estimators.
  Basics of testing hypothesis. Testing hypothesis in R language.
  Regression analysis in R language.

MV013 Statistics for Computer Science

zk 2/2 3 kr., jaro

• doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
• Prerequisities: The knowledge of basic calculus, linear algebra and theory of probability.
• Goals: The main goal of the course is to become familiar with some basic principles of data science and statistics, with writing about numbers (presenting data using basic characteristics and statistical graphics), some basic principles of likelihood and statistical inference; to understand basic probabilistic and statistical models; to understand and explain basic principles of parametric statistical inference for continuous and categorical data base on Wald principle, likelihood and score principle connecting the statistical theory with implementation in R, geometry, and statistical graphics; to implement these techniques to R language; to be able to apply them to real data.
• Learning outcomes: Student will be able:
  - to understand principles of likelihood and statistical inference for continuous and discrete data;
  - to select suitable probabilistic and statistical model for continous and discrete data;
  - to use suitable basic characteristics and statistical graphics for continous and discrete data;
  - to build up and explain suitable statistical test for continuous and discrete data;
  - to apply statistical inference on real continuous and discrete data;
  - to apply simple linear regression model including ANOVA on real continuous data;
  - to implement statistical methods of continuous and discrete data to R.
• Syllabus: Why computer scientists should study statistics?
  Computer science related problems with analysed data
  Why the thought study based on data is useful?
  Data types
  Sampling
  Parametric probabilistic and statistical models
  Likelihood principle and parameter estimation using numerical methods
  Descriptive statistics (tables, listings, figures)
  From description to statistical inference
  Hypothesis testing and parameters of a model
  Goodness-of-fit tests
  Testing hypotheses about one-sample
  Testing hypotheses about two-samples
  Testing hypotheses about more than two sample problems including ANOVA
  Simple linear regression model
  Interpretation of statistical findings

IB000 Mathematical Foundations of Computer Science

zk 2/2 4 kr., podzim

• prof. RNDr. Petr Hliněný, Ph.D.
• Goals: This course is focused on understanding basic mathematical concepts necessary for study of computer science. This is essential for building up a set of basic concepts and formalisms needed for other theoretical courses in computer science. At the end of this course the successful students should: know the basic mathematical notions; understand the logical structure of mathematical statements and mathematical proofs, specially mathematical induction; know discrete mathematical structures such as finite sets, relations, functions, and graph; be able to precisely formulate their claims, algorithms, and relevant proofs; and apply acquired knowledge in other CS courses as well as in practice later on.
• Learning outcomes: After finishing the course the student will be able to: understand the logical structure of mathematical statements and mathematical proofs, deal with and explain basic structures of discrete mathematics, precisely formulate their claims, algorithms, and relevant proofs.
• Syllabus: The course focuses on understanding basic mathematical tools:
  Basic formalisms - statements, proofs, and propositional logic.
  Sets, relations, and functions.
  Proof techniques, mathematical induction.
  Recursion, structural induction.
  Binary relations, closure, transitivity.
  Equivalence and partial orders.
  Composition of relations and functions.
  Basics of graphs, isomorphism, connectivity, trees.
  Graph distance, spanning trees. Directed graphs.
  Proof techniques for algorithms.
  Infinite sets and the halting problem.

IB002 Algorithms and data structures I

zk 2/2 4 kr., jaro

• prof. RNDr. Ivana Černá, CSc.
• Prerequisities: IB001 || IB111 || IB999
  The students should comprehend the basic notions on the level of IB111 Introduction to Programming and IB000 Mathematical Foundations of Computer Science Students should be able to: understand and apply basic constructs of programming languages (e.g., conditions, loops, functions, basic data types) in Python, know principles of recursion, and several basic algorithms. Students should know the basic mathematical notions; understand the logical structure of mathematical statements and mathematical proofs, specially mathematical induction; know discrete mathematical structures such as finite sets, relations, functions, and graph including their applications in informatics.
• Goals: The course presents basic techniques of the analysis of algorithms, data structures, and operations. Students should correctly apply the basic data structures and algorithms as well as apply the algorithm design and analysis techniques when designing new algorithms. Students implement their algorithms in programming language Python.
• Learning outcomes: After enrolling the course students are able to:
  - actively use and modify basic sorting algorithms and graph algorithms,
  - actively used basic techniques for designing algorithms (divide et impera, recursion) and design simple algorithms,
  - actively used and modify basic static and dynamic data structures,
  - employ time complexity and correctness of algorithms,
  - analyze time complexity and prove the correctness of simple iterative and recursive algorithms,
  - implement algorithms in the selected programming language (Python).
• Syllabus: Basic analysis of algorithms: The correctness of algorithms, input and output conditions, partial correctness, convergence, verification.
  Length of computation, algorithm complexity, problem complexity. Asymptotical analysis of time and space complexity, growth of functions.
  Algorithm design techniques. Divide et impera and recursive algorithms.
  Fundamental data structures: lists, queues. Representation of sets, hash tables. Binary heaps. Binary search trees, balanced trees (B trees, Red-black trees).
  Sorting algorithms: quicksort, mergesort, heapsort, lower bound for the time complexity of sorting.
  Graphs and their representation. Graph search. Depth-first traversal, topological sort, strongly connected components. Breadth-first traversal, bipartite graphs. Shortest paths, algorithm Bellman-Ford, Dijkstra's algorithm.

IB005 Formal Languages and Automata

zk 2/2 4 kr., jaro

• prof. RNDr. Mojmír Křetínský, CSc.
• Prerequisities: IB000 && ! IB102
  Knowlegde corresponding to the courses IB000 Mathematical Foundations of Computer Science
• Goals: Students should be able to understand and explain the rich heritage of models and abstractions that have arisen over the years, and to develop the students' capacity to form abstractions of their own and reason in terms of them.
• Learning outcomes: At the end of the course students should be able to:
  Demonstrate an in-depth understanding of theories, concepts and techniques in automata and their link to computation.
  Develop abstract machines that demonstrate the properties of physical/SW systems and be able to specify the possible inputs, processes and outputs of these machines. Analyze the computational strengths and weaknesses of these machines.
  Understand the concept of computability by manipulating these machines in order to demonstrate the properties of computational processes.
  Practice techniques of program design and development by using abstract machines. Apply automata concepts and techniques in designing systems that address real world problems
• Syllabus: Languages and grammars. Chomsky hierarchy.
  Finite automata and regular grammars.
  Properties of regular languages. Applications.
  Context-free grammars and pushdown automata.
  Properties of context-free languages.
  Turing machines (TM). Computable languages and functions, LBA. Properties of recursive and recursive enumerable languages.
  Undecidability, halting problem for TM, Reduction, Post Correspondece Problem, undecidable problems from language theory.

IB015 Non-Imperative Programming

zk 2/1 4 kr., podzim

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: There are no special prerequisities apart from the basic math skills (on the secondary-school level), and certain aptitude for abstract reasoning.
• Goals: On successful completion of the course, students will understand functional and logic programming paradigms. Programming languages enforcing declarative way of description of an algorithm bring on programming habits that the students will be able to use in practice later on when implementing large applications using even imperative languages.
• Learning outcomes: After graduation students will: - understand fundaments of functional programming, - be able to decompose computational problems to individual functions and apply this ability for design and implementation of programs even in imperative programming languages, - have basic knowledge of Haskell programming language - be able to design and implement recursive functions, - be able to work with recursively defined data structures.
• Syllabus: Functional computational paradigm and Haskell
    Functions in programming;
    Lists, Types and Recursion
    Functions of higher rank, Lambda functions
    Accumulators, Type definitions, Input/Output
    Reduction strategy, Infinite lists
    Relation of recursion and induction, Recursive data types
    Time complexity of computation, Type classes, Modules
    Functional solutions od some problems
  
  Logical computational paradigm and Prolog
    Non-imperative programming in Prologu
    Lists, Arithmetics, Tail rekursion in Prologu
    Cuts, Input-Output, All solutions
    An Introduction to Constraint Solving Programming

IB016 Seminar on Functional Programming

z 0/2 2 kr., jaro

• Vladimír Chlup - Martin Kurečka - Bc. Adam Matoušek - RNDr. Vladimír Štill
• Prerequisities: IB015
  Pre-requisities for enrolling in the course are to be familiar with Haskell in the scope of the IB015 Non-Imperative Programming course and to have a positive attitude towards functional programming.
• Goals: Students will significantly extend their knowledge of functional programming. At the end of the course, they should be able to solve non-trivial programming problems using Haskell and be familiar with practical use of this functional language.
• Learning outcomes: After finishing the course, the student will be able to:
  — write a Haskell program with approximatelly 100 to 200 lines;
  — perform analysis and functional decompisition of given problem;
  — use supportive tools for Haskell developers such as the Cabal package manager, the Hackage package repository, the HLint linter, and the QuickCheck testing framework;
  — describe theoretical functional concepts;
  — have an idea about some more advanced functional techniques used in practice.
• Syllabus: Advanced syntax, modules, custom type classes, advanced data structures.
  Package system (Hackage/Stackage), support tools (Cabal, HLint, Haddock).
  Functors, applicative functors, monads.
  Automatic generation of tests according to program specification (QuickCheck).
  Input and output in Haskell, processing errors and exceptions (Maybe, Either, exceptions, error states).
  Semigroups, monoids, the Foldable and Traversable classes.
  Evaluation strategies (laziness vs. strictness).
  Context-aware traversal of data structures (Zippers, Lens).
  Monadic parsing (Parsec).
  Monads for shared writing, shared reading and keeping the state (Writer, Reader, State).
  Monad transformers (MaybeT, ErrorT).
  Processing strings and other useful GHC extensions.
  Haskell in real world projects.

IB030 Introduction to Computational Linguistics

zk 2/0 2 kr., jaro

• doc. RNDr. Aleš Horák, Ph.D.
• Goals: In this course the main principles of natural language processing are presented. The algorithmic description of the main language analysis levels will be discussed - morphology, syntax, semantics and pragmatics. Also the resources of natural language data, corpora, will be presented. The role of knowledge representation, inference and relations to artificial intelligence will be touched as well.
• Learning outcomes: Students will be able to:
  - identify and summarize the main phases of computer natural language analysis;
  - describe principles of algorithms used for speech analysis;
  - explain the main approaches to analysis at the morphological and syntactic level of language;
  - provide an overview of main language resources, their formats and processing;
  - understand approaches to computational semantics and its applications.
• Syllabus: Introduction to Computational Linguistics (Natural Language Processing, NLP).
  Levels of description: phonetics and phonology, morphology, syntax, semantics and pragmatics.
  Representation of morphological and syntactic structures.
  Analysis and synthesis: speech, morphological, syntactic, semantic.
  Knowledge representation forms with regard to lexical units.
  Language understanding: sentence meaning representation, logical inference.

IB031 Introduction to Machine Learning

zk 2/2 3 kr., jaro

• doc. RNDr. Tomáš Brázdil, Ph.D. - doc. RNDr. Lubomír Popelínský, Ph.D.
• Prerequisities: Recommended courses are MB102 a MB103.
• Goals: By the end of the course, students should know basic methods of machine learning and understand their basic theoretical properties, implementation details, and key practical applications. Also, students should understand the relationship among machine learning and other sub-areas of mathematics and computer science such as statistics, logic, artificial intelligence and optimization.
• Learning outcomes: By the end of the course, students
  - will know basic methods of machine learning;
  - will understand their basic theoretical properties, implementation details, and key practical applications;
  - will understand the relationship among machine learning and other sub-areas of mathematics and computer science such as statistics, logic, artificial intelligence and optimization;
  - will be able to implement and validate a simple machine learning method.
• Syllabus: Basic machine learning: classification and regression, clustering, (un)supervised learning, simple examples
  Decision trees: learning of decision trees and rules
  Logic and machine learning: specialization and generalization, logical entailment
  Evaluation: training and test sets, overfitting, cross-validation, confusion matrix, learning curve, ROC curve; sampling, normalisation
  Probabilistic models: Bayes rule, MAP, MLE, naive Bayes; introduction to Bayes networks
  Linear regression (classification): least squares, relationship wih MLE, regression trees
  Kernel methods: SVM, kernel transformation, kernel trick, kernel SVM
  Neural networks: multilayer perceptron, backpropagation, non-linear regression, bias vs variance, regularization
  Lazy learning: nearest neighbor method; Clustering: k-means, hierarchical clustering, EM
  Practical machine learning: Data pre-processing: attribute selection and construction, sampling. Ensemble methods. Bagging. Boosting. Tools for machine learning. Weka.
  Advanced methods: Inductive logic programming, deep learning.

IB047 Introduction to Corpus Linguistics and Computer Lexicography

zk 2/0 2 kr., jaro

• doc. Mgr. Pavel Rychlý, Ph.D.
• Goals: A basic introduction to the field of corpus linguistics and computational lexicography. Students will study types of corpora, corpus building and usage, especially in the sake of dictionaries building.
• Learning outcomes: Student will be able to: choose the right korpus type for specific purpose; interpret all layers of corpus annotation; use statistical methods on text corpora; design the structure of a dictionary; use free tools for dictionary writing.
• Syllabus: Information technologies and language (text) corpora. Beginning of corpus linguistics, purpose of corpora.
  Corpus data, corpus types and their standardization, SGML, XML, TEI, CES. Annotated corpora, tagging on various levels: structural tagging, grammatical tagging -- POS, lemmata, word forms. Syntactic tagging, treebanks, skeleton analysis. Parallel corpora, alignment. Tools for automatic and semi-automatic annotation, disambiguation.
  Building corpora, maintenance. Corpus tools: corpus manager. Concordance programmes. Queries, regular expressions and their use. Statistical programmes, absolute and relative frequencies, MI and T-score. Work with corpus attributes and tags.
  Working with corpora -- CNC, SUSANNE, Prague Dependency Treebank
  Words, constructions, collocations.
  Computational lexicography, lexicology.
  Descripton of meanings (semantic features).
  Types of computer dictionaries. Lexicography standards.
  Data for dictionary building -- corpora.
  Lexicography Software tools. Lemmatizers.

IB053 Efficient Programming Methods

k 1/1 2 kr., jaro

• Mgr. Petr Steinmetz
• Prerequisities: Knowledge of programming at some of languages C, C++, Pascal, Delphi, Java, C#; knowledge of object oriented programming; basic awareness of machine code
• Goals: Purpose of this lecture is to forward knowledge and experiences needed to development of software. A term "efficient programming" is here meant in two sense. Partly as work expended on creation of program that is to be efficient as possible and partly as program self whose implementation is also to be efficient as possible, i.e. so that computer while performs program makes minimum overhead (noneffective activity). Subject of lecture is not algorithm design self in term of complexity.
• Learning outcomes: At the end of course student gains knowledge and routine leading to more efficient creation of software including more efficient implementation od algorithm.
• Syllabus: Work efficiency in algorithm design.
  Cutback of error rate in program creation.
  Cutback of time needed to elimination of mistakes.
  Usage of earlier written parts of programs.
  Independence of program from later changes.
  Portability of program to other environment.
  Program efficiency.
  Data access mechanism.
  Implementation of program structures.
  Difference in interpreted and compiled languages.

IB107 Computability and Complexity

zk 2/1 3 kr., podzim

• doc. RNDr. Jan Strejček, Ph.D.
• Prerequisities: IB005 || IB102
  
• Goals: The course introduces basic approaches and methods for classification of problems with respect to their algorithmic solvability. It explores theoretical and practical limits of computers usage and consequences these limitations have for advancing information technologies.
  At the end of the course the students will be able: to understand basic notions of computability and complexity; to understand the main techniques used to classify problems (reductions, diagonalisation, closure properties), and to apply them in some simple cases.
• Learning outcomes: After enrolling the course student will be able to:
  - use asymptotic notation, both actively and passively;
  - explain difference between complexity of an algorithm and of a problem;
  - independently decide to which complexity class a given problem belongs;
  - do practical decisions based on a complexity classification of a particular problem;
  - explain that some problems are not computable, give examples of such problems;
  - explain the difference between various classes of not-computable problems;
• Syllabus: Algorithms and models of computation. Church thesis.
  Classification of problems. Decidable, undecidable and partially decidable problems. Computable functions.
  Closure properties. Rice theorems.
  Computational complexity. Feasible and unfeasible problems. Polynomial computational thesis.
  Reduction a completeness in problem classes. Many-one reduction and polynomial reduction. Complete problems with respect to decidability, NP-complete problems. Applications.

IB109 Design and Implementation of Parallel Systems

zk 2/0 2 kr., jaro

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: The knowledge of low-level programming in C is expected at the level PB071.
• Goals: The goal of this course is to introduce to students the principles of design and implementation of parallel systems and get them acquainted with the programmer's means for their development.
• Learning outcomes: On successful completion, students should understand the principles of design and implementation of parallel algorithms and should have limited experience with programmer's means for their development. In particular, students should be able to design and implement their own parallel applications, they should know how to use selected libraries supporting the development of parallel applications, and should be able to explain what is behind the API calls to such libraries.
• Syllabus: Motivation for parallel computing. Parallel algorithm design -- decomposition and communication. Analyzes of parallel algorithms. Parallel algorithms in shared-memory.OpenMP, Intel TBB. POSIX Threads. Lock-free algorithmics. Parallel algorithms in distributed-memory. Message Passing Interface (MPI). Examples of parallel graph algorithms. Parallel algorithms for many-core platforms.

IB110 Introduction to Informatics

zk 2/2 3 kr., jaro

• RNDr. Petr Novotný, Ph.D.
• Prerequisities: ! IB102 && ! IB005
  none
• Goals: The main objective of the course is to acquaint the students with basic abstract computational models and their use in analysis of algorithms and computational problems. At the end of the course, the students will understand fundamental concepts in the theory of finite automata, computability and complexity theory. They will be able to leverage the knowledge of these concepts for deeper understanding of concepts appearing in a practice of programming.
• Learning outcomes: Successful course graduates will be able to:
  - explain the notion of a finite automaton and construct finite automata for simple regular languages
  - explain the notion of a regular expression and construct REs for simple regular languages
  - explain the concept of non-determinism and use non-determinism to simplify the construction of finite automata
  - use the basic algorithms for handling of finite automata (determinisation etc.)
  - understand the notion of decidability and explain the existence of undecidable problems
  - explain the concept of a Turing machine and construct TMs for simple problems
  - understand the concept of reduction between computational problems
  - understand the concept of computational complexity, the basic complexity classes and relationships between them
• Syllabus: Finite automata and regular languages. Construction of finite automata.
  Non-deterministic automata, the use of non-determinism, determinisation, minimalisation.
  Regular expressions and regular grammars. Examples of non-regular languages.
  Computational problems and algorithms. Turing machines. Decidable and undecidable problems, diagonalisation.
  Reductions between computational problems.
  Time and space complexity of algorithms and problems. Classes P and NP. NP-complete problems. Examples of complexity classes and relationships between them.

IB111 Foundations of Programming

zk 2/2 4 kr., podzim

• RNDr. Nikola Beneš, Ph.D.
• Prerequisities: ! IB113 && ! NOW ( IB113 )
  
• Goals: The course is an introduction to programming and algorithmic style of thinking.
• Learning outcomes: At the end of the course students should be able to: understand and apply basic constructs of programming languages (e.g., conditions, loops, functions, basic data types); write and debug a program in Python; use basic data types and structures (strings, lists, dictionaries); describe several basic algorithms; describe main conventions and recommended programming style.
• Syllabus: Basic constructions of imperative programming languages: conditions, loops, data types, functions, input, output.
  Number types, randomness, algorithms with numbers.
  Data types, lists, dictionaries, objects.
  Basic algorithms: prime numbers, sorting, searching. Complexity of algorithms (basics).
  Recursion.
  Turtle graphics, bitmap graphics, text processing.

IB113 Introduction to Programming and Algorithms

zk 2/2 4 kr., podzim

• doc. Mgr. Radek Pelánek, Ph.D.
• Prerequisities: ! NOW ( IB111 ) && ! IB111 && ! PB162 && ! PB161 && ! PB071 && ! IB001
  
• Goals: The course is an introduction to programming and algorithmic style of thinking. At the end of the course students should be able to: understand and apply basic constructs of programming languages (e.g., conditions, loops, functions, basic data types) and know several basic algorithms.
• Learning outcomes: After finishing this course, a student should be able to:
  - use basic tools of structured imperative programming languages (variables, conditions, loops, functions, record data types);
  - write and debug a simple Python program and adhere to recommended principles of programming style;
  - use basic data types and structures (strings, lists, dictionaries);
  - explain several classical algorithms.
• Syllabus: Basic constructions of imperative programming languages: conditions, loops, data types, functions, input, output.
  Number types, randomness, algorithms with numbers.
  Data types, lists, dictionaries, objects.
  Basic algorithms: prime numbers, sorting, searching. Complexity of algorithms (basics).
  Turtle graphics, bitmap graphics, regular expressions, text processing.

IB114 Introduction to Programming and Algorithms II

zk 2/1 3 kr., jaro

• prof. RNDr. Ivana Černá, CSc.
• Prerequisities: IB113 && ! IB002 && ! NOW ( IB002 )
  This course is intended for non-informatics students. The others are recommended IB002 instead.
• Goals: The course presents basic data structures and algorithms. Students should correctly apply the basic data structures and algorithms as well as apply the algorithm design and analysis techniques when designing new algorithms. Students implement their algorithms in programming language Python.
• Learning outcomes: After enrolling the course students are able to:
  - actively use basic sorting algorithms and graph algorithms,
  - actively design simple algorithms,
  - actively used basic static and dynamic data structures,
  - employ time complexity and correctness of algorithms,
  - implement algorithms in the selected programming language (Python).
• Syllabus: Basic analysis of algorithms. The correctness of algorithms, input and output conditions, partial correctness, convergence, verification.
  Length of computation, algorithm complexity, problem complexity. Asymptotical analysis of time and space complexity, growth of functions.
  Fundamental data structures. Lists, queues. Representation of sets, hash tables. Binary heaps. Binary search trees.
  Sorting algorithms. Quicksort, Mergesort, Heapsort.
  Graphs and their representation. Graph search. Depth-first traversal and Breadth-first traversal, applications.

IA006 Selected topics on automata theory

zk 2/1 3 kr., podzim

• prof. RNDr. Mojmír Křetínský, CSc.
• Prerequisities: Knowlegde corresponding to the courses IB005 - Formal languages and automata and IB107 - Computability and complexity
• Goals: The main aim is to understand and explain selected advanced parts of automata theory, including parsing techniques for deterministic contex-free languages, relationship between finite-state automata and MSO logic, automata on infinite words, and process specifications. Further, students should be able to make reasoned decisions about computational models appropriate for the respective areas and to understand methods and techniques of their applications.
• Learning outcomes: At the end of the course students should be able to understand and explain selected advanced parts of automata theory, and to make reasoned decisions about computational models appropriate for the respective area and to understand methods and techniques of their applications.
• Syllabus: Methods of syntactic analyses of detCFLs.
  LL(k) grammars and languages, properties and analyzers.
  LR(k) grammars and languages, properties and analyzers.
  Relationships between LL, LR and detCFL.
  Infinite=state transition systems and nondeterminism - bisimulation. Selected decidable problems related to process verification.
  Finite-state automata and monadic second-order logic
  Automata and infinite words: infinite words, regular (rational) sets of infinite words.
  Automata: deterministic and nondeterministic Buchi automata, Muller, Rabin, and Street automata. McNaughton theorem. Relationships.

IA008 Computational Logic

zk 2/2 3 kr., podzim

• Dr. rer. nat. Achim Blumensath - doc. RNDr. Lubomír Popelínský, Ph.D.
• Goals: At the end of the course students should be familiar with main research and applications in computational logic; They will be able to use automatic provers for propositional and predicate logic and also for its extensions; They will be familiar with, and able to use, methods for inductive inference in those logics;
• Learning outcomes: After successfully completing this course students should be familiar with several logics, including propositional logic, first-order logic, and modal logic. They should be familiar with various proof calculi for these logics and be able to use such calculi to test formulae for satisfiability and or validity. In addition, they should have basic knowledge about automatic theorem provers and they way these work.
• Syllabus: Resolution for propositional logic.
  Resolution for first-order logic.
  Prolog.
  Fundamentals of database theory.
  Tableaux proofs for first-oder logic.
  Natural deduction.
  Induction.
  Modal logic.
  Many-valued logics.

IA010 Principles of Programming Languages

zk 2/0 2 kr., jaro

• Dr. rer. nat. Achim Blumensath
• Prerequisities: Knowledge of at least one imperative (e.g. C/C++/Java) and one functional language (e.g. Haskell). Knowledge of additional programming languages is an advantage.
• Goals: By the end of the course, the student will be able:
  to understand the various features of a given programming language , including their advantages and disadvantages;
  to choose a programming language and programming paradigm suitable for a given problem domain;
  to analyse both strong and weak aspects of a given programming language;
  to quickly obtain an in-depth understanding a of new programming language;
• Learning outcomes: After successfully completing this course students will be familiar with the most common features of programming languages. They will know how these features can be used. They will be able to discuss which features can be used to solve a given programming problem and the advantages and disadvantages of the various options.
• Syllabus: Brief history of programming languages.
  Expressions and functions. Scoping. Functional programming.
  Types and type checking. Polymorphism. Type inference.
  State and side effects. Imperative Programming.
  Modules. Abstract data types.
  Control flow. Continuations. Generators. Exceptions. Algebraic effects.
  Declarative Programming. Single assignment variables. Unification. Backtracking.
  Object oriented programming. Dynamic Dispatch. Subtyping. Encapsulated state. Inheritance.
  Concurrency. Fibres. Message passing. Shared memory.

IA011 Programming Language Semantics

zk 2/1 3 kr., jaro

• prof. RNDr. Antonín Kučera, Ph.D.
• Prerequisities: Students should be familiar with basic notions of set theory and formal logic (validity and provability, correctness and completeness of deductive systems, etc.)
• Goals: An introduction to the theory of formal semantics of programming languages (operational, denotational, and axiomatic semantics).
• Learning outcomes: After graduation, student will:
  understand basic types of formal semantics of programming languages;
  be able to reason about properties of programs using formal semantics;
  understand basic notions of temporal logics.
• Syllabus: Formal semantics of programming languages, basic paradigms (operational, denotational, and axiomatic approach).
  Structural operational semantics and its variants (small-step and big-step semantics).
  Denotational semantics. Complete partial orders, continuous functions. The fixed-point theorem and its applications, semantics of recursion. Equivalence of operational and denotational semantics.
  Axiomatic semantics. Hoare's deductive system, its correctness and completeness.
  Temporal logics; the semantics of non-terminating and parallel programs.

IA012 Complexity

zk 2/0 2 kr., podzim

• prof. RNDr. Ivana Černá, CSc.
• Prerequisities: The course expands on course IB107 Computability and Complexity.
• Goals: Theory of computational complexity is about quantitative laws and limitations that govern computing. The course explores the structure of the space of of computable problems and develops techniques to reduce the search for efficient methods for the whole class of algorithmic problems to the search for efficient methods for a few key algorithmic problems. The theory classifies problems according to their computational complexity into feasible and unfeasible problems. Finally, the course tries to understand unfeasability can be coped with the help of techniques like randomization, approximation and parallelization. The main goal of the course is to provide a comfortable introduction to moder complexity theory. While choosing the relevant topics, it places premium on choosing topics that have a concrete relationship to algorithmic problems. Students should understand and analyze complexity issues of basic algorithmic problems and compare different computing approaches.
• Learning outcomes: After enrolling the course students are able to:
  - actively work with computational complexity of problems and algorithms,
  - analyse upper and lower bounds of computational complexity,
  - differentiate between tractable and untractable problems,
  - define basic complexity classes and analyze their relationships,
  - explain (NP) hardness and prove hardness of computational problems,
  - describe limits of determicnistic, nondeterministic, alternating, randomized, and parallel computing paragigms.
• Syllabus: The structure and properties of time complexity classes. Relation between determinism and nondeterminism.
  The structure and properties of space complexity classes. Relation between determinism and nondeterminism. closure properties of space complexity classes.
  Unfeasible problems. Hierarchy of complexity classes. Polynomial hierarchy. Relativization. Non-uniform computational complexity.
  Randomized complexity classes and their structure. Approximative complexity classes and non-approximability.
  Alternation and games. Interactive protocols and interactive proof systems.
  Lower bounds techniques. Kolmogorov complexity.
  Descriptive complexity.

IA014 Advanced Functional Programming

zk 2/0 2 kr., jaro

• doc. Mgr. Jan Obdržálek, PhD.
• Prerequisities: Previous experience with functional programming, at least to the extent covered by the course IB015 - Non-imperative programming.
• Goals: Introduce the underlying theory of functional programming. Show some of the modern advanced functional programming concepts (monads, monad transformers, GADTs, dependent types...).
• Learning outcomes: By the end of the course, students will:
  understand the theoretical foundations of functional programming, e, g, lambda calculi and type theory;
  understand and be able to efficiently use modern/advanced concepts of functional programming languages (e.g. typeclasses, monads, monad transformers...);
  know the limits of the functional programming paradigm;
  be able to evaluate and use FP-based concepts in modern mainstream (non-FP) languages
• Syllabus: History of functional programming languages.
  Untyped lambda calculus.
  Simply typed lambda calculus.
  Polymorphism add type inference (Hindley-Milner, System F)
  Type classes.
  Functors, Applicatives.
  Monads.
  Monad tranformers.
  GADTs - Generalized Algebraic Data Types
  Dependent types.
  IO and Concurrency.

IA023 Petri Nets

zk 2/0 2 kr., jaro

• prof. RNDr. Antonín Kučera, Ph.D.
• Prerequisities: Students should be familiar with basic notions of computability, complexity, and automata theory.
• Goals: An introduction to Petri nets; the course covers both "classical" results (about boundedness, liveness, reachability, coverability, etc.) and "modern" results (the (un)decidability of equivalence-checking and model-checking, etc.)
• Learning outcomes: At the end of the course, students should be able to: understand the language of Petri nets; model various classes of systems using Petri nets; apply specific analytical techniques developed for Petri nets; prove properties of discrete systems using Petri nets and appropriate specification formalisms.
• Syllabus: The theory of Petri nets provides a formal basis for modelling, design, simulation and analysis of complex distributed (concurrent, parallel) systems, which found its way to many applications in the area of computer software, communication protocols, flexible manufacturing systems, software engineering, etc.
  Principles of modelling with Petri nets.
  Classical results for place/transition nets. Boundedness, coverability, Karp-Miler tree, weak Petri computer; reachability and liveness.
  (Un)decidability of equivalence-checking and model-checking with place/transition nets.
  S-systems, T-systems. Reachability, liveness, S-invariants, T-invariants.
  Free-choice Petri nets. Liveness, Commoner's theorem.

IA038 Types and Proofs

zk 2/0 2 kr., jaro

• prof. RNDr. Jiří Zlatuška, CSc.
• Goals: This course delivers focuses on the correspondence between proof theory and typed lambda-calculus and its generalization to the correspondence between computations as proof simplifications and program specifications as types in various formal settings. The contents of the course is relevant for work in many areas of theoretical computer science.
• Syllabus: Meaning and denotation in logic, tarski and Heyting.
  natural deduction: calculus, rules, computational interpretation.
  Curry-Howard isomorphism: lambda-calculus, operational and denotational interpretation, conversion, isomorphism.
  Normalization theorem: Church-Rosser property, weak normalization, strong normalization.
  Sequent calculus: structural rules, intuitionistic version, identities, logical rules, properties of the cut-free system, translation between sequent calculus and natural deduction.
  Strong normalization theorem: reducibility and its properties.
  Gödels system T, calculus, normalization, expressive power.
  Coherent spaces, stabil functions, paralel disjunction, product and function spaces, denotational semantics of System T.
  Sums in natural deduction: problems, standard conversion, commuting conversions, functional calculus.
  System F: calculus, simple types, free structures, inductive types, Curry-Howard isomorphism, strong normalization.
  Coherent semantics of the sum; cut-elimination theorem; representation.

IA040 Modal and Temporal Logics for Processes

zk 2/0 2 kr., podzim

• prof. RNDr. Luboš Brim, CSc.
• Prerequisities: Recommended: IV010 Communication and Parallelism
• Goals: The aim is to acquire basic knowledge and develop skills in the use of modal and temporal logics for specification, analysis and verification of computer systems.
  By the end of the semester, students should be able:
  to understand definitions of the logics and logical systems presented in the course, the ideas of the proofs;
  to understand the differences in the logics, and their capabilities and limitations;
  to understand the utility, potential and limitations of formal verification, in particular model checking, for linear-time and branching-time logics.
• Learning outcomes: By the end of the semester, students should be able: • to understand and apply definitions of the logics and logical systems presented in the course, the ideas of the proofs; • to understand the differences in the logics, and their capabilities and limitations; • to understand the utility, potential and limitations of formal verification, in particular model checking, for linear-time and branching-time logics.
• Syllabus: Modal logics: propositional modal logic, modal mu-calculus.
  Temporal logics: propositional temporal logic, linear and branching time, temporal operators.
  Classification of properties, liveness, safety, local and global properties.
  Model checking, applications.

IA046 Computability

zk 2/0 2 kr., jaro

• prof. RNDr. Luboš Brim, CSc.
• Prerequisities: SOUHLAS
  Prerequisities: IB107 Computability and Complexity, M4155
• Goals: The course is focused on deeper understanding of results in the computability theory with emphasis on methods and techniques used to prove such results.
  At the end of the course the students will be able to understand basics of computability over real numbers; will get acquainted with additional results about classification of computational problems, in particular about arithmetical hierarchy and relativised theory of computability.
• Syllabus: Recursion theorem, generalized Rice theorem, Rogers isomorphism theorem.
  Application to logic. Arithmetical sets and functions, Goedel-Rosser incompleteness theorem. Goedel's second incompleteness theorem.
  Relativised computability. Programs with oracles.
  Kleene hierarchy, Turing reducibility, tt-reducibility, arithmetical hierarchy.
  Post's problem.
  Analytical hierarchy.
  Computability on real numbers, complete partial orders, domains.

IA062 Randomized Algorithms and Computations

zk 2/2 3 kr., jaro

• prof. RNDr. Jozef Gruska, DrSc.
• Prerequisities: No special requirements are needed.
• Goals: The aim: randomized algorithms and methods are becoming one of the key tools for an effective solution of a variety of problems in informatics and its aplications practically in all theoretical and aplication areas.
• Learning outcomes: After finishing the lecture student will be able: To manage basic techniques to design randomized algorithms; to understand differences concerning power of deterministic and randomized algorithms; to manage basic tools for analysis of randomized algorithms; to work with tail inequalities; to understand power and use of the probabilistic method; to understand power of random walks; to understand power of randomized proofs; to understand basic principles of randomized cryptographic protocols.
• Syllabus: Randomized algorithms and methods.
  Examples of randomized algorithms.
  Methods of game theory.
  Main types of randomized algorithms.
  Randomized complexity classes.
  Chernoff's bounds.
  Moments and deviations.
  Probabilistic methods.
  Markov chains and random walks.
  Algebraic methods.
  Aplications:
  Linear programming.
  Parallel and distributed algoritms.
  Randomization in cryptography.
  Randomized methods in theory of numbers.

IA066 Introduction to Quantum Computing

zk 2/0 2 kr., podzim

• prof. RNDr. Jozef Gruska, DrSc.
• Prerequisities: MB003 && ( IB005 || IB102 )
  linear algebra, automata and languages, no quantum physics is necessary, algorithm design
• Goals: Quantum computing in particular and quantum information processing in general are one of the hotest subjects in science in general and in informatics in particular. The goal of this introductory course is to present basic aims, concepts, methods and result in this fascinating area.
• Learning outcomes: After completing the course student will be able: to understand principles of the design of quantum algorithms; to understand basic ideas of Shor's and Grover's algorithms; to design simple quantum circuits; to understand recognition power of several quantum automata; to understand basic principles of quantum cryptography - theory, experiment and practical systems; to design quantum error-correcting codes.
• Syllabus: Motivácie, historia, základné kvantové experimenty, ohraničenia a paradoxy kvantového spracovania informácie
  Hilbertové priestory, kvantové bity, registre, hradla a obvody
  kvantové výpočtové primitíva
  kvantové entanglovanie a nelokálnost
  jednoduché kvantové algoritmy, Shorove kvantové algoritmy, algoritmus Grovera a jeho aplikácie
  kvantové konečné automaty
  kvantové samoopravujúce kody a kvantové fault-tolerantné hradla.
  kvantová krzptografia
  vesmír ako kvantový systém

IA067 Informatics Colloquium

z 1/0 1 kr., podzim

• prof. RNDr. Jozef Gruska, DrSc.
• Goals: The aim of the colloquium is to present new directions, methods and results in informatics, broadly understood. Talks will cover all areas of informatics and related areas and will be given by well-known specialists, especially outside of Brno and from abroad.
• Learning outcomes: After finishing the course students will have updated information about recent research provided by faculties and also by specialists from other academic instituition, also from abroad. For each presented area student will be able to decide whether its techniques can be used to solve a particular theoretical or application problem.
• Syllabus: The aim of the colloquium is to present new directions, methods and results in informatics, broadly understood. Talks will cover all areas of informatics and related areas and will be given by well-known specialists, especially outside of Brno and from abroad.

IA067 Informatics Colloquium

z 1/0 1 kr., jaro

• prof. RNDr. Jozef Gruska, DrSc.
• Goals: The aim of the colloquium is to present new directions, methods and results in informatics, broadly understood. Talks will cover all areas of informatics and related areas and will be given by well-known specialists, especially outside of Brno and from abroad.
• Learning outcomes: After finishing the course students will have updated information about recent research provided by faculties and also by specialists from other academic instituition, also from abroad. For each presented area student will be able to decide whether its techniques can be used to solve a particular theoretical or application problem.
• Syllabus: The aim of the colloquium is to present new directions, methods and results in informatics, broadly understood. Talks will cover all areas of informatics and related areas and will be given by well-known specialists, especially outside of Brno and from abroad.

IA072 Seminar on Verification

z 0/2 2 kr., podzim

• doc. RNDr. Jan Strejček, Ph.D.
• Prerequisities: souhlas
  for postgraduate students; undergraduate students interested in formal methods may ask for an exception, especially if they are interested in program analysis or automata theory.
• Goals: The aim of the course is to
  introduce students to selected research areas;
  check their ability to understand a scientific paper;
  check and improve their skill of presenting a scientific paper;
• Learning outcomes: At the end of the course students should be able to:
  understand a theoretical scientific text;
  make a presentation that explains main ideas of such a text;
  potentially apply gathered knowledge in an original research;
• Syllabus: Presentations of results from the following areas:
  Analysis and verification of software.
  Automata and logics over infinite words.
  Satisfiability and theorem proving.

IA072 Seminar on Verification

z 0/2 2 kr., jaro

• doc. RNDr. Jan Strejček, Ph.D.
• Prerequisities: souhlas
  for postgraduate students; undergraduate students interested in formal methods may ask for an exception, especially if they are interested in program analysis or automata theory.
• Goals: The aim of the course is to
  introduce students to selected research areas;
  check their ability to understand a scientific paper;
  check and improve their skill of presenting a scientific paper;
• Learning outcomes: At the end of the course students should be able to:
  understand a theoretical scientific text;
  make a presentation that explains main ideas of such a text;
  potentially apply gathered knowledge in an original research;
• Syllabus: Presentations of results from the following areas:
  Analysis and verification of software.
  Automata and logics over infinite words.
  Satisfiability and theorem proving.

IA077 Advanced Quantum Information Processing

zk 2/0 2 kr., jaro

• prof. RNDr. Jozef Gruska, DrSc.
• Prerequisities: IA066
  Prerequisities: course IA066 Introduction to quantum computing or agreement with the lecturer
• Goals: To present advanced basic concepts of quantum information processing to such an extend that participants could get involved in research in this area. Lecture should be of interest and importance especially to those with a deeper interest in quantum information processing: projects, diploma thesis, doctarate study.
• Learning outcomes: Understanding and ability to use basic terms such as entropy, quantum canals. Understanding and ability to explain fundaments of quantum entangling.
• Syllabus: Mixed states and density matrices, quantum operations and their representations, projective and POVM measurements and their applications
  quantum information theory -- entropies, quantum channel capacities
  quantum entanglement and multipartite quantum entanglement (structure, measures, sharing laws and limitations), quantum error correction and fault-tolerant systems
  quantum non-locality
  new paradigms in quantum information processing.

IA080 Seminar on Knowledge Discovery

k 0/2 2 kr., podzim

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Goals: At the end of the course students should be able to understand scientific works in the area of machine learning and knowledge discovery in data and use it in their work. They will be able to evaluate contributions of such research studies.
• Learning outcomes: A student will be able
  - to understand research papers from machine learning and data mining;
  - of critical reading of such papers;
  - to prepare and present a lecture on advanced methods of data science.
• Syllabus: The seminar is focused on machine learning and theory and practice of knowledge discovery in various data sources. Program of the seminar contains also contributions of teachers and PhD. students of the Knowldge Discovery Laboratory, as well as other laboratories, on advanced topics of knowledge discovery.

IA080 Seminar on Knowledge Discovery

k 0/2 2 kr., jaro

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Prerequisities: Prerequisite for enrollment in the subject is 1) being familiar with advanced machine learning 2) approval of the application by the teacher
• Goals: At the end of the course students should be able to build and evaluate advanced machine learning systems and to understand scientific works in the area of machine learning and data science and use it in their work. They will be able to evaluate contributions of such research studies.
• Learning outcomes: A student will be able
  - to understand research papers from machine learning and data mining;
  - of critical reading of such papers;
  - to prepare and present a lecture on advanced methods of data science.
• Syllabus: The seminar is focused on machine learning and theory and practice of knowledge discovery in various data sources. Program of the seminar contains also contributions of teachers and PhD. students of the Knowldge Discovery Laboratory, as well as other laboratories, on advanced topics of knowledge discovery.

IA082 Physical concepts of quantum information processing

zk 2/0 2 kr., jaro

• doc. Mgr. Mário Ziman, Ph.D.
• Prerequisities: PV275 || SOUHLAS
  
• Goals: Introduction to quantum physics and quantum information theory.
• Learning outcomes: After this course students should:
  understand basic principles of quantum physics;
  apply the learned concepts in the subsequent study of quantum information theory;
  self-study quantum theory books.
• Syllabus: 1. Security and computation with photons - photon's polarization and polarizers, Vernam cipher, quantum key "distribution" protocol B92, polarizing beam-splitter, √NOT logic gate,
  2. Quantum interference and superposition - Mach-Zender interferometer, concept of quantum state, quantum probabilities and amplitudes, Hilbert space and operators,
  3. Measuring quantum properties - description of quantum measurement devices (POVM), tomography of polarization, uncertainty relations, no information without disturbance
  4. Hydrogen atom - emission spectrum, Bohr's model, position and momentum, quantum solution, Zeeman effects, spin of electron,
  5. Schrodinger equation - time and evolution, unitary operators, energy conservation and system's Hamiltonian,
  6. Quantum bit - two-level quantum system (polarization and spin-1/2), Stern-Gerlach experiments, Bloch sphere, orthogonality and information, no-cloning theorem, quantum NOT gate, qubit implementations
  7. Quantum sources and randomness - mixed states, quantum commpression, von Neumann entropy, capacity of noiseless quantum channel, randomness sources, min-entropy
  8. Einstein-Podolski-Rosen paradox - composite quantum systems, tensor product, quantum steering, EPR paradox, local hidden variable model, CHSH inequalities, experiments and loopholes
  9. Quantum one-time pad protocols - one-time pad, super-dense coding and teleportation
  10. Quantum entanglement - correlated and separable states, definition of entanglement, entanglement distilation,
  11. Quantum cryptography - QKD protocols BB84, E91, no-quantum bit commitment theorem, quantum secret sharing protocols,
  12. Elementary particles - fermions and bosons and tensor products, standard model, Higg's boson

IA101 Algorithmics for Hard Problems

zk 2/0 2 kr., podzim

• prof. RNDr. Ivana Černá, CSc.
• Prerequisities: Experience with basic techniques for design and analysis of algorithms (recursion, dynamic programming, greedy approach) as well as with basic data structures and algorithms are required.
• Goals: The course expands on courses IB002 Algorithms and Data Structures I and IV003 Algorithms and Data Structures II. It focuses on design of algorithms for hard computing tasks. The course systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems like randomization, heuristics, approximation and local search.
• Learning outcomes: After enrolling the course students are able to :
  - identify algorithmically hard problems,
  - identify applications where pseudopolynomial, approximative, randomized, and heuristic algorithms can be succesfully used,
  - actively used published pseudopolynomial, approximative, and randomized algorithms and correctly interpret their outcomes,
  - design simple pseudopolynomial, approximative, and randomized, algorithms,
  - experimentally evaluate heuristic algorithms.
• Syllabus: Deterministic approaches: pseudo-polynomial-time algorithms, parametrized complexity, branch-and-bound, lowering worst case complexity of exponential algorithms.
  Approximation approaches: concept of approximation algorithms, classification of optimization problems, stability of approximation, inapproximability, algorithms design. Linear programming as a method for construction of approximative algorithms.
  Randomized approaches: classification of randomized algorithms and design paradigms, design of randomized algorithms, derandomization, randomization and approximation.
  Heuristics: local search, simulated annealing, genetic algorithms.

IA158 Real Time Systems

zk 2/0 3 kr., jaro

• doc. RNDr. Tomáš Brázdil, Ph.D.
• Prerequisities: Basic programming skill in C is expected.
• Goals: At the end of the course students should: know specific aspects of real-time systems; understand main problems of the design of real-time systems and know some solutions; be able to use formal reasoning about real-time systems.
• Learning outcomes: At the end of the course student will have a comprehensive knowledge of real time systems and related areas. Will be able to distinguish basic types of real-time systems. Will be aware of typical design errors in real-time and embedded systems and their standard solutions. Will understand fundamental real-time scheduling and resource management algorithms. Will have a basic knowledge of implementation details of these algorithms in standard programming environments.
• Syllabus: Real-time aspects of embedded systems; examples of real-time systems. Soft and hard real-time systems.
  Real-time scheduling: periodic and aperiodic tasks, priority-driven scheduling, resource access control.
  Basic information about real-time operating systems and programming.

IA159 Formal Verification Methods

zk 2/0 2 kr., jaro

• doc. RNDr. Jan Strejček, Ph.D.
• Prerequisities: IV113 || IA169
  
• Goals: At the end of this course, students should understand and be able to explain principles, advantages, and disadvantages of selected methods from the area of formal verification, namely model checking methods, abstraction, static analysis via abstract interpretation, and shape analysis;
  make reasoned decisions about suitability of various methods for verification of specific systems;
• Learning outcomes: At the end of this course, students should understand and be able to explain principles, advantages, and disadvantages of selected methods from the area of formal verification, namely model checking methods, abstraction, static analysis via abstract interpretation, and shape analysis;
  make reasoned decisions about suitability of various methods for verification of specific systems;
• Syllabus: Overview of formal verification methods.
  LTL model checking of finite and infinite-state systems including partial order reduction.
  Abstraction.
  Counterexample-guided abstraction refinement (CEGAR).
  Static analysis, abstract interpretation.
  Shape analysis.
  Software verification via automata, symbolic execution, and interpolation.
  Property-Directed Reachability (PDR/IC3).

IA161 Advanced Techniques of Natural Language Processing

k 1/1 2 kr., podzim

• doc. RNDr. Aleš Horák, Ph.D. - RNDr. Miloš Jakubíček, Ph.D. - RNDr. Marek Medveď - RNDr. Zuzana Nevěřilová, Ph.D. - Mgr. Vít Nováček, PhD - RNDr. Adam Rambousek, Ph.D. - RNDr. Vít Suchomel
• Prerequisities: All students should have basic practical knowledge of programming in Python. Overview knowledge of the natural language processing field at the level of introductory courses such as IB030 Introduction to Computational Linguistics or PA153 Natural Language Processing is expected.
• Goals: The course participants will have the opportunity to learn about, test and experiment with advanced techniques of natural language processing (NLP) and to develop an understanding of the limits of those techniques. The course aims to introduce current research issues, and to meet in practice with particular programming techniques used in language technology applications.
• Learning outcomes: After studying the course, the students will be able to:
  - explain a selected NLP problem and list its main aspects;
  - implement a basic or intermediate application for complex tasks in language processing, typically for Czech, Slovak, or English;
  - create data resources (models, test sets) for a selected NLP problem and evaluate their assets;
  - compare selected available tools for complex NLP tasks and apply them to chosen data resources with possible adaptations to particular purposes.
• Syllabus: The presented NLP problems will concentrate on practical problems connected with processing human-produced textual data. Particular topics include:
  
• Opinion mining, sentiment analysis
• Machine translation
• Parsing of Czech: Between Rules and Statistics
• Named Entity Recognition
• Building Language Resources from the Web (effective crawling, boilerplate removal, tokenisation, near duplicates identification)
• Language modelling
• Topic identification, topic modelling
• Extracting structured information from text
• Automatic relation extraction (hypernyms, synonyms, ...)
• Adaptive electronic dictionaries
• Terminology identification (keywords, key phrases)
• Anaphora resolution
• Stylometry
• Automatic language corrections

IA168 Algorithmic game theory

zk 2/0 2 kr., podzim

• doc. RNDr. Tomáš Brázdil, Ph.D.
• Prerequisities: basic linear algebra, basic probability theory (mostly discrete probability), elementary complexity theory, some calculus
• Goals: In recent years, huge amount of research has been done at the borderline between game theory and computer science, largely motivated by the emergence of the Internet. The aim of the course is to provide students with basic knowledge of fundamental game theoretic notions and results relevant to applications in computer science. The course will cover classical topics, such as general equilibrium theory and mechanism design, together with modern applications to network routing, scheduling, online auctions etc. We will mostly concentrate on computational aspects of game theory such as complexity of computing equilibria and connections with machine learning.
• Learning outcomes: Student knows the basics types of models of games and algorithms for searching winning strategies.
• Syllabus: Basic definitions: Games in normal form, dominant strategies, Nash equilibria in pure and mixed strategies, existence of Nash equilibria, basic examples
  Computing Nash equilibria: Lemke-Howson algorithm, support enumeration, sampling methods, PPAD-completeness of Nash equilibria,
  Quantifying the inefficiency of equilibria and related games: Congestion and potential games, price of anarchy and price of stability, routing games, network formation games, load balancing games
  Learning in games: Regret minimization algorithms, correlated equilibria and connection to learning in games, regret minimization in routing games
  Auctions and mechanism design: First price auctions, Vickrey auctions, truthfulness, Vickrey-Clark-Groves mechanism, Bayesian games, Bayesian Nash equilibria, formal framework for mechanism design, revelation principle, auctions on Google
  Games with multiple moves: Games in extensive form, games on graphs, Markov decision processes, stochastic games

IA169 System Verification and Assurance

zk 2/0 4 kr., podzim

• prof. RNDr. Jiří Barnat, Ph.D. - doc. RNDr. Vojtěch Řehák, Ph.D. - prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
• Prerequisities: (! IV113 ) && (! NOW ( IV113 ))
  User-level familiarity with Unix/Linux operating system. Basics of C programming. Basic astract math reasoning.
• Goals: The student will understand the necessary theoretic background as well as acquire hands-on experience with relevant tools for bug finding and formal verification techniques. With the help of a tutor students will get acquainted with a number of concrete software verification tools for analysis of concurrent systems, real-time systems, hybrid systems, cryptographic systems and systems with probabilities.
• Learning outcomes: Students will:
  be aware of fundaments of black-box testing;
  understand priciples of deductive verification;
  understand the theory and application of model checking;
  have hand-on experince with a couple of verification tools.
• Syllabus: This course will provide the necessary theoretic background as well as hands-on experience with relevant tools for bug finding and formal verification techniques. An introductory insight into security standards like Common Criteria for Information Technology Security Evaluation and FIPS 140 shall be provided first, together with a discussion of security threat models. Following this, the core topics of this course will include testing, simulations, advance testing and symbolic execution, abstract interpretation, static analysis, theorem proving, automated formal verification as well as an introduction to model-based verification. With the help of a tutor students will get acquainted with a number of concrete software verification tools for analysis of concurrent systems, real-time systems, hybrid systems, cryptographic systems and systems with probabilities.

IV003 Algorithms and Data Structures II

zk 2/2 3 kr., jaro

• prof. RNDr. Ivana Černá, CSc.
• Prerequisities: ( IB002 || program ( PřF:N - MA )) && ! IB108
  The course expands on courses IB002 Algorithms and Data Structures I.
• Goals: The course expands on the introductory course Algortihm Design I. It presents algorithmic concepts without their direct connection to any particular programming language. The aim is to introduce students into design and analysis of advanced algorithms. The course presents advanced techniques of algorithm analysis and a wide spectrum of strategies together with algorithms built up on these strategies. Students are introduced into new data structures which are displayed in a row with algorithms based on them.
• Learning outcomes: After enrolling the course students are able to:
  - actively use and modify advanced graph and string algorithms,
  - actively used advanced techniques for designing algorithms (dynamic programming, greedy techniques) for designing algorithms, expain their specific properties and limits,
  - actively used and modify advanced dynamic data structures and use them for designing effective algorithsm,
  - analyze time complexity and prove correctness of algorithms.
• Syllabus: Advanced design and analysis techniques: dynamic programming, greedy strategies,backtracking. Amortized analysis.
  Advanced data structures: binomial and Fibonacci heaps, data structures for disjoint sets.
  Graph algorithms: Single-Source Shortest Paths (The Bellman-Ford algorithm). All-Pairs Shortest Paths (Shortest paths and matrix multiplication, The Floyd-Warshall algorithm, Johnson's algorithm for sparse graphs). Maximum Flow (The Ford-Fulkerson method, The Push-Relabel method). Maximum bipartite matching.
  String matching: the naive string-matching algorithm, Karp-Rabin algorithm, string matching with finite automata. The Knuth-Morris-Pratt algorithm.

IV010 Communication and Parallelism

zk 2/0 2 kr., jaro

• prof. RNDr. Luboš Brim, CSc.
• Goals: The goal is to acquire basic skills that are used for formal specification and analysis of communicating systems, including the theoretical background.
  By the end of the course the students should be able: to develop simple specifications and implementations of communicating systems in CCS, to check formally their equivalence and to understand various kinds of process equivalences and their limitations.
• Learning outcomes: By the end of the course the students should be able: to develop simple specifications and implementations of communicating systems in CCS, to check formally their equivalence and to understand various kinds of process equivalences and their limitations.
• Syllabus: Introduction, overview of models for concurrent systems. Modelling communication, examples of communicating systems.
  Language of CCS: synchronization, actions and transitions, internal communication, semantics of CCS.
  CCS with value passing and its translation into pure CCS.
  Equational laws and their applications: classification of combinators, expansion theorem, dynamic and static laws.
  Bisimulation and equivalence: Strong bisimulation, weak bisimulation, weak congruence, basic properties, solving equations, other equivalences, finite state processes.
  Temporal properties of processes.

IV022 Design and verification of algorithms

zk 2/0 2 kr., jaro

• prof. RNDr. Luboš Brim, CSc.
• Goals: The goal is to get acquaint with methods for design and verification of small sequential algorithms. The students acquire basic verification techniques.
• Learning outcomes: By the end of the semester, students should be able to develop small sequential algorithms and prove their correctness.
• Syllabus: Programs as predicate transformers, weakest precondition, properties of predicate transformers, program correctness.
  Garded command language. Skip and abort commands, composition, alternative command, iterative command.
  Verification of programs, proof outlines, verification rules for sequential composition, alternative, and loop commands. Array manipulation.
  Constructive verification of programs, basic principles and strategies, developing loops from invariants and bounds, developing invarinats.
  Examples of program development. Deriving of efficient algorithms, Searching and sorting.

IV029 Introduction to Transparent Intensional Logic

zk 2/0 2 kr., podzim

• prof. RNDr. Marie Duží, CSc.
• Prerequisities: Foundations of the first-order predicate logic
• Goals: Students enrolled in the course will obtain knowledge on a rather new discipline Logical semantics and knowledge representation that belongs to the fundamentals of artificial intelligence.
  Adequate analysis of the meaning of natural language expressions consists in discovering algorithmically structured procedure known as TIL construction encoded by the expression. The analysis should be as fine-grained as possible so that the inference machine is neither over-inferring nor under-inferring. At the same time it is necessary to formalize the results of an analysis so that they are computationally tractable.
• Learning outcomes: The students will learn to solve relevant problems in such a way that undesirable paradoxes and inconsistencies are avoided. The formalized analysis can be used in knowledge-base systems of artificial intelligence, in automatic translation, in multi-agent systems, etc.
• Syllabus: Deductive reasoning as the subject of logic
  Paradoxes stemming from a coarse-grained analysis of premises
  Frege-Church semantic schema; denotational vs. procedural semantics
  Transparent Intensional Logic; constructions as procedures
  Simple theory of types comprising non-procedural objects; epistemic base; intensions and extensions
  Ramified theory of types comprising procedural objects
  Extensional, intensional and hyperintensional context
  Extensional rules: Leibniz’s law and existential quantification into
  The problem of non-existence and modalities
  Ontology as a logic of intensions; conceptual analysis
  Logic of attitudes; hyperintensional knowledge representation
  Dynamic reasoning and tense logics
  Communication of agents in a multi-agent system

IV054 Coding, Cryptography and Cryptographic Protocols

zk 2/1 5 kr., podzim

• prof. RNDr. Jozef Gruska, DrSc.
• Prerequisities: Basics of linear algebra and of the theory of numbers
• Goals: The lecture deals with the basic methods to solve three key problems of the transmission of information. All three problems are of large practical importance and their solutions are based on elegant theoretical results.
• Learning outcomes: On successful completion of the course students should be able to: understand problems of the theory of error-correcting codes; understand basic principles and results of the theory of secure communication; know principles and problems of basic cryptosystems for encryption (both secret and public key), digital signing and authentication; know methods to create core cryptographic protocols primitives; analyze and practically use simple cryptosystems; be experienced in methods of quantum cryptography and steganography
• Syllabus: Coding theory and modern cryptography are rich on deep, elegant, interesting and practically very important ideas, methods, and systems. Main concepts of modern cryptography are closely connected with fundamental concepts of theoretical informatics. Current cryptography and its methods and systems are of key importance for modern communication and information systems. Basic knowledge of coding methods and of modern cryptography are necessary for each graduate of informatics.
  Lecture will be rich also on examples and experiences from a very rich and interesting history of cryptography.
  Basic concepts of coding theory
  Linear codes
  Cyclic and channel codes
  Classical cryptography
  Public-key cryptosystems, knapsack, RSA, public key exchange
  Other cryptosystems and cryptographic primitives
  Digital signatures
  Elliptic curves in cryptography and integer factorization
  Basic cryptographic protocols
  Authentication, identification, secret sharing, e-commerce
  Steganography and watermarking
  From crypto-theory to crypto-practice
  Quantum cryptographic protocols
  Machines and history of cryptography

IV057 Seminar on Information Society

k 0/2 2 kr., podzim

• prof. RNDr. Jiří Zlatuška, CSc.
• Prerequisities: Students can only register for this course after presenting a two-page long (approx. 4kB) essay on their ideas concerning the notion of Information Society.
• Goals: At the end of the course, students should be able to understand better issues related to the information society, gain deeper insight into more specialized topics, and to develop their own ability to interpret technological and social issues related to the information society.
• Learning outcomes: Ability to think about impacts of IT on society.
• Syllabus: Seminar focuses on some aspects of the Information Society. A loose companion seminar to IV064 Information Society based on students work with literature on this topic and talks by the students based on the literature. Studets are required to work independently with relevant literature.
  Information technologies and the society.
  Information as a real value.
  Economic and social impact.
  Civilizational impacts of the Information Society.
  Information technologies and democracy.

IV057 Seminar on Information Society

k 0/2 2 kr., jaro

• prof. RNDr. Jiří Zlatuška, CSc.
• Goals: At the end of the course, students should be able to understand better issues related to the information society, gain deeper insight into more specialized topics, and to develop their own ability to interpret technological and social issues related to the information society.
• Learning outcomes: Ability to think about impacts of IT on society.
• Syllabus: Seminar focuses on some aspects of the Information Society. A loose companion seminar to IV064 Information Society based on students work with literature on this topic and talks by the students based on the literature. Studets are required to work independently with relevant literature.
  Information technologies and the society.
  Information as a real value.
  Economic and social impact.
  Civilizational impacts of the Information Society.
  Information technologies and democracy.

IV064 Information Society

zk 2/0 2 kr., podzim

• prof. RNDr. Jiří Zlatuška, CSc.
• Goals: The goal of this course is to introduce the nature of wider impacts of Informatics on the society.
• Learning outcomes: At the end of this course students will be able to understand and explain the nature of wider impacts of Informatics on the society; to use information about events characteristic for the impact of the information revolution; to draw parallels with the industrial revolution; to explain and characterize events and processes associated with the formation of information society; to better comprehend the role of the information and communication technologies in the society not only as technical tools, but also as a phenomenon enabling social processes transformation; to understand newly emerging organizational structures both in business and in e-government resulting from intensification of the information processing; to understand the nature of innovative processes associated with informatics and to thing through the consequences of differencec from prevailing older paradigms; to grasp idea of the structure of policies assiciated with information society; to present thoughful analyses of nontechnical impacts of widespread availability and use of services based on information processing; to think through and creatively develop designs of new possible applications; to develop motivation for future theoretical or practical work in this area.
• Syllabus: This course deals with the impact of Information Technologies on society, with the nature of computer (information) revolution, and the advent of an information society.
  Informatics in historical perspective.
  Computer revolution.
  Productivity paradox.
  The Internet and WWW.
  Digital economy.
  Network economy and virtual communities.
  Organizational and company structure.
  Organizational transformation.
  Teleceoomunications and information infrastructure.
  Legal aspects of an information society.
  Ethical problems.
  Riskc of computing technology.
  Social impacts.
  There is a seminar IV057 Seminar on Information Society accompanying this course for students interested in presenting up-to-date material based on literature on an information society.

IV074 Laboratory of Parallel and Distributed Systems

z 0/0 2 kr., podzim

• prof. RNDr. Jiří Barnat, Ph.D. - prof. RNDr. Ivana Černá, CSc.
• Prerequisities: souhlas
  Applicants should 1) be able to work independently 2) have interest in long-term projects (several semesters) 3) have working knowledge of English 4) be able to work in a team. The enrollment must be approved by the laboratory head (J. Barnat).
• Goals: The goal of this course is to let students participate on research activities.
• Learning outcomes: On successful completion of the course students - will have practical experience with active research - should be able to read and understand scientific papers - should be able to employ gathered information to formulate and prove their own hypotheses within the relevant context.
• Syllabus: Laboratory of Parallel and Distributed Systems (ParaDiSe) is a team project focused on the development of parallel methods and tools for the design and analysis of complex systems. Students meet regularly with senior researchers to discuss research problems related to their research topics.

IV074 Laboratory for Parallel and Distributed Systems

z 0/0 2 kr., jaro

• prof. RNDr. Jiří Barnat, Ph.D. - prof. RNDr. Ivana Černá, CSc.
• Prerequisities: souhlas
  Applicants should 1) be able to work independently 2) have interest in long-term projects (several semesters) 3) have working knowledge of English 4) be able to work in a team. The enrollment must be approved by the laboratory head (J. Barnat).
• Goals: The goal of this course is to let students participate on research activities.
• Learning outcomes: On successful completion of the course students - will have practical experience with active research - should be able to read and understand scientific papers - should be able to employ gathered information to formulate and prove their own hypotheses within the relevant context.
• Syllabus: Laboratory of Parallel and Distributed Systems (ParaDiSe) is a team project focused on the development of parallel methods and tools for the design and analysis of complex systems. Students meet regularly with senior researchers to discuss research problems related to their research topics.

IV100 Parallel and distributed computations

zk 2/0 2 kr., podzim

• prof. RNDr. Ivana Černá, CSc. - prof. RNDr. Rastislav Královič, Ph.D.
• Prerequisities: IB002
  IB002 (Design of algorithms), required. PB152 (Operating systems) recommended.
• Goals: The aim of the course is to introduce students into the field of distributed computation. It presents the basic concepts, problems and solutions. Algorithms for selected group of problems give the insight into the techniques used in the field and show how the various environments influence the quality and (un)solvability of the problem.
• Learning outcomes: Students will know particular algorithms for distributed routing, leader election and termination.
• Syllabus: Distributed systems and distributed algorithms.
  Communication protocols. Alternating-bit protocol, sliding-window protocol.
  Routing algorithms. Routing tables and algorithms for their constructions. Floyd-Warshallův algorithm, shortest-path algorithm.
  Distributed mutual exclusion. Distributed election algorithms. Ring networks and a general topology. Impact of synchrony. Impact of sense of direction.
  Termination detection. Dijkstra-Scholten algorithm.
  The problem of Byzantine generals and its (un)solvability in various environments.

IV105 Bionformatics seminar

k 0/1 1 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: Those who sign up for this interdisciplinary course should be able to read and comprehend a scientific paper or book chapter written in English. Alternatively computational tools in bioinformatics will be studied. Deeper knowledge of algorithm design and programming will allow the particular student to focus more on the biological side of the studied problems or vice versa. Students of non-biological fields should be concurrently enrolled in, or have previously passed IV107 Bioinformatics I. Alternatively they may frequent the course with the consent of the teacher.
• Goals: The Fall Term seminar (P series) will be titled "Prediction of protein function and structure from sequence". The course will convene for 1hr weekly.
• Learning outcomes: Students will gain insight into problems studied in bioinformatics; they will practice presentation and discussion techniques in front of an audience.
• Syllabus: The students will chose publications to study recent methods in genomic sequence analysis (using suggested journal articles or other material approved by the teacher).
  Protein structure and function prediction from sequence
  Similarity of protein molecules
  Signalling and metabolic pathway analysis and visualization

IV106 Bioinformatics seminar

k 0/1 1 kr., jaro

• Ing. Matej Lexa, Ph.D.
• Prerequisities: Those who sign up for this interdisciplinary course should be able to read and comprehend a scientific paper or book chapter written in English. Deeper knowledge of algorithm design and programming will allow the particular student to focus more on the biological side of the studied problems or vice versa. Students of non-biological fields should be concurrently enrolled in, or have previously passed IV107 Bioinformatics I. Alternatively they may frequent the course with the consent of the teacher.
• Goals: The Spring Term seminar covers "Biological sequence analysis, protein structure prediction, detection of genes, promoter sequences and other elements".
• Learning outcomes: Students will gain insight into problems studied in bioinformatics; they will practice presentation and discussion techniques in front of an audience.
• Syllabus: Students will chose publications to study recent methods in genomic sequence analysis (using suggested journal articles or other material approved by the teacher). Possible subjects of papers:
  Sequencing data processing
  Gene identification in DNA sequences
  Similarity between sequences
  Motif and pattern searching
  DNA and RNA secondary structure prediction

IV107 Bioinformatics I

zk 2/1 2 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: This is an entry course into the area of bioinformatics for students of non-biological disciplines, there are no prerequisites.
• Goals: This course will lead the students into the fascinating world of molecules, genes and proteins. Currently, bioinformatics is going through a period of unusual growth. Abilities to think and act as a bioinformatician (to work with large biological datasets using modern computer science methods) are needed in many areas of science and applied disciplines, especially biology, medicine and chemistry.
• Learning outcomes: After taking the course, the students will understand basic principles of molecular biology; they will be familiar with important biological problems that can be best handled by computers; they will understand and be able to choose basic computational methods for handling molecular data.
• Syllabus: The history and subject of bioinformatics
  Basics of molecular biology
  Organization of living matter
  DNA structure and function
  Protein structure and function
  Evolution of genes and proteins
  Bioinformatic data
  Data sources
  Common data types
  Public sequence data and their accessibility
  DNA sequence analysis
  Computer exercises: Data sources, similarity search, visualization of molecules
  Protein sequence analysis
  Structural and functional data
  Similarity searches and scoring
  Other types of data and their analysis
  Expression data
  Protein digests and mass spectra
  Literature data analysis

IV108 Bionformatics II

zk 1/1 2 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: IV107 Bioinformatics I or consent of the teacher (not needed for biology students).
• Goals: Introduction to selected algorithms and methods of analysis used in bioinformatics.
• Learning outcomes: At the end of the course, the students will:
  understand the inner workings of selected algorithms, their advantages and disadvanteges, including knowledge of recent alternatives
  be able to work with 3-D models of molecules
  be able to evaluate or design methods for solving current problems in bioinformatics
  understand the principles of existing DNA sequencing methods and processing sequencing data
• Syllabus: Algorithms for sequence analysis
  Algorithms for prediction and analysis of structural data
  Biological language
  Next-generation DNA sequencing methods and data processing
  Understanding protein cleavage and mass spectra
  Expression profile and promoter analysis

IV109 Modeling and Simulation

zk 2/1 3 kr., jaro

• doc. Mgr. Radek Pelánek, Ph.D.
• Goals: The course offers a wide overview of computational modeling and gives students a practical experience with computational modeling.
• Learning outcomes: At the end of the course students will be able to: describe main concepts of complex systems (particularly "feedback loops"); explain main principles and applications of computational modeling; compare modeling approaches; describe well-know case studies in computational modeling; create a computational model.
• Syllabus: Introduction, history, role of modeling and simulation in research, applications. Computational models.
  Complex systems, system thinking, feedback loops.
  System dynamics approach, examples (demographics, Limits to growth).
  Agent based modeling: basic principles, cellular automata, decentralized systems.
  Game theory, models of cooperation. Models of adaptation (genetic algorithms, neural networks).
  Modeling of networks: examples of networks and their properties, models of networks.
  Analysis and evaluation of models.
  Application of modeling from different areas (e.g. economics, traffic, epidemiology, biology).

IV110 Bionformatics project I

k 1/1 2 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
• Goals: In this course the students will:
  be able to select appropriate bioinformatic tools for a given problem
  be able to carry out independent analysis of bioinformatic data
  present their results to their colleagues
• Learning outcomes: In this course the students will:
  be able to select appropriate bioinformatic tools for a given problem
  be able to carry out independent analysis of bioinformatic data
  present their results to their colleagues
• Syllabus: Discussion of interesting problems to solve
  Preparation of student proposals
  Programming phase
  Student mini-conference

IV111 Probability in Computer Science

zk 2/2 3 kr., podzim

• doc. RNDr. Vojtěch Řehák, Ph.D.
• Prerequisities: Knowledge of basic discrete mathematics (e.g. as presented in the course IB000).
• Goals: At the end of the course student should have a broad knowledge and an ability of independent study of problems based on the probability theory and its computer science applications. Will be able to apply the results of the probability theory in practical examples. Should be able to learn independently new problems requiring knowledge of probability theory. Will be able to characterise basic principles of data compression and error correction. Should be able to apply information theory results in practice.
• Learning outcomes: Student is able: to define basic terms of the mentioned topics (e.g., random variable, expectation, variance, random process, Markov chain, channel capacity, code rate); to explain meaning on the terms on practical examples; to solve simple examples e.g. using linearity o expectation; to provide basic analysis on both discrete- and continuous-time Markov chains; to compute (conditional) expectation, mutual information, and entropy random variables with given probability distribution; to demonstrate basic proof mentioned during lectures.
• Syllabus: Probability. Discrete probabilistic space.
  Random variable and its applications. Expectation and variation.
  Markov and Chebyshev inequalities. Chernoff bounds. Weak and strong law of large numbers.
  Random processes. Markov processes.
  Entropy. Information.
  Applications in computer science (information theory, coding theory, cryptography etc).

IV112 Project on programming parallel applications

z 0/5 5 kr., podzim

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: A participant is expected to be familiar with concepts of threads and processes, parallelism and is also expected to have some programming skills in C, or C++.
• Goals: The goal of the course is to expose students to a couple of problems related to parallel programing and let them solve these problems individualy.
• Learning outcomes: Students will gain practical experience with programming of parallel aplications and solutions of related algorithmic problems.
• Syllabus: Initial kick-off meeting; definition of projects and deadlines; work on the projects; final discussion.

IV114 Bioinformatics and Systems Biology Project

k 0/1 2 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: The students should have finished IV107 Bioinformatics I and have elementary programming skills in any programming language/environment (optimally UNIX with C/C++/Java and Perl/Python) or consent of the lecturer
• Goals: In this course the students will:
  be able to select appropriate bioinformatic tools for a given problem
  be able to carry out independent analysis of bioinformatic data
  present their results to their colleagues
• Learning outcomes: In this course the students will:
  be able to select appropriate bioinformatic tools for a given problem
  be able to carry out independent analysis of bioinformatic data
  present their results to their colleagues
• Syllabus: Discussion of interesting problems to solve
  Preparation of student proposals
  Programming phase
  Student mini-conference

IV115 Parallel and Distributed Laboratory Seminar

z 0/2 2 kr., podzim

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: souhlas
  Ability of self-education by reading latest scientific papers focused on modeling and verification of complex systems.
• Goals: Students acquire experience with preparing presentations of their own research work and should be able to actively participate in research activities of the ParaDiSe laboratory.
• Learning outcomes: Experience with presentation of research results to adequately educated audience.
• Syllabus: Discussion topics and papers to be studied and presented are specified during the first two weeks of semester.

IV115 Parallel and Distributed Laboratory Seminar

z 0/2 2 kr., jaro

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: souhlas
  Ability of self-education by reading latest scientific papers focused on modeling and verification of complex systems.
• Goals: Students acquire experience with preparing presentations of their own research work and should be able to actively participate in research activities of the ParaDiSe laboratory.
• Learning outcomes: Experience with presentation of research results to adequately educated audience.
• Syllabus: Discussion topics and papers to be studied and presented are specified during the first two weeks of semester.

IV119 Seminar on Discrete Mathematical Methods

k 0/2 2 kr., jaro

• prof. RNDr. Petr Hliněný, Ph.D. - prof. RNDr. Daniel Kráľ, Ph.D., DSc.
• Prerequisities: Basics of undergraduate mathematics (IB000 is enough).
• Goals: The aim of this seminar is to introduce interested students into the beauties of mathematics and of clean mathematical proofs. This will teach students "mathematical thinking" - to understand math definitions, statements, and proofs in their full depth, and to make their own new proofs in all areas of mathematics and theoretical computer science.
• Learning outcomes: After finishing this seminar, successful students should be able to understand presented mathematical proofs in their full depth, and to make their own new proofs in areas of mathematics and theoretical computer science.
• Syllabus: Selected nice topics from "Proofs from THE BOOK"; TBA each year.
  Number theory, Combinatorics, Combinatorial geometry, Graph theory.
  Different topics are chosen in subsequent years.

IV121 Computer science applications in biology

zk 2/1 3 kr., jaro

• Ing. Matej Lexa, Ph.D. - doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: The course has no specific initial requirements. The goal is to inform students and young researchers of life sciences about several opportunities to apply computer scientific techniques in their field.
• Goals: The main aim of the course is to bridge the gaps between computer science and life sciences by presenting the selected theoretical problems solved in computer science After absolving the course students should be able to:
  understand selected parts of computer science that make a tool for life sciences;
  get a comprehensive overview of computational tools and techniques relevant for life sciences;
  get basic knowledge of selected software tools (ability to execute programs and to use their elementary features).
• Learning outcomes: After absolving the course students should be able to:
  define the contribution of computer science for biology and biomedicine;
  associate relevant tools and techniques with selected set of biological problems;
  use selected tools at basic level and apply them to simple models.
• Syllabus: 1. Introduction to bioinformatics and systems biology
  2. Discrete dynamic models and their analysis; hands-on NetLogo, SPiM
  3. Continuous dynamic models and their analysis; hands-on Stella, COPASI
  4. Regulatory networks, metabolic and signaling networks; hands-on Cytoscape, Biocarta
  5. Similarity searching; hands-on MS, VMATCH
  6. Processing NGS sequencing data
  7. 3D geometry, CSG; hands-on: PovRay, Pymol/Chimera
  8. Final lecture (conclusions and discussion)

IV123 Informatics-Driven Future

zk 2/0 2 kr., jaro

• prof. RNDr. Jozef Gruska, DrSc.
• Prerequisities: There are no special technical requirements. Main requirement is a deeper interest to know the expected role of Informatics for society in future, , as well as its main challenges and potential
• Goals: Exponentially fast developments in Informatics, especially in information storing, transmission and processing driven technologies, and in artificial intelligence, create potential for enormous impacts on society. The impact that has potential to be very positive, but also very negative, even historical. Moreover, due to that development, what can be nowadays expected as to happen in the next 50-100 years, in most of the areas of society, especially in science, technology, health care,...., if the current rate of development is sustained, can happen actually already within next 20-40 years. The goal of the course is to provide a visionary and thoughts-provoking, but well grounded, analysis of the main developments that we can, reasonably, expect, and why, in the (very) near future. Especially due to the development in all information processing and communication driven technologies, nanotechnologies, genetics, non-biological (artificial) intelligence and in fights with natural death and in explorig intelligence as a commodity. Informatics, once properly understood and developed%and sufficiently broadly and deeply understood, is to play at that a key role. Merits of the favorable future, but also ways to avoid perils, if possible, will also be discussed. The course should be of interest and importance to all those interested to find out the frameworks, tools, tasks and main challenges they and society will face in the (already quite near) future. To understand that should be for anyone not only very interesting, but actually much needed for knowing how to prepare oneself in the best way for the expected long future carrier in enormously fast changing frameworks. Contents: 1. Introduction: Why and how to foresee future? Main megachallenges. 2. Evolution - from biological to non-biological one and to their merge. 3. Exponential acceleration of all information-driven technologies. 4. New perception of Scientific Informatics and its grand challenges. 5. Impulses and roads to a new perception of Informatics 6. Technological and Applied Informatics and their grand challenges. 7. New, Informatics-driven, methodology and its grand challenges. 8. Developments in the understanding and simulation of human brains. 9. GNR-revolution - Artificial intelligence and robotics,aibeings 10. GNR revolution - Genetics and Nanotechnologies. 11. Singularity: merge of bio- and non-bio-intelligence-merits/perils. 12. Longevity - Can we fight death? Can we make life enjoyable till/after 150?!
• Learning outcomes: Understanding of unpredictability of impact of IT evolution to the future.
• Syllabus: 1. Introduction. Why and how we need/can forsee future? Old and new mega-challenges of science, technology and informatics. 2.Evolution. From biological to non-biological (technological) evolution and their merge. Enormous expected impacts of the merge ot the biological and non-biological intelligence. 3. Exponential developments in information processing and communication technologies and their impacts on science, technology and the rest of society 4.New perception of informatics and its grand challenges. Informatics as a merge of scientific, engineering, methodological and application informatics. New perception of the scientific informatics and its grand challenges. 5. New perception of the technological iand applied nformatics and their grand challenges. 6. New, informatics-driven methodology for science, technology, and actually for all areas of society. 7. Recent developments in understanding and simulation of human brains and minds 8. GNR revolution - I. Robotics and artificial intelligence. Long hhistory, hot outcomes, big dangers. 9. GNR Revolution - II. Geniomics and nanotechnologies 10. Singularity - a merge of biological and non-biological evolution. 12. Longevity - Can we fight death? How (much). Can we make life ebjyable till/after 150?!

IV125 Formela lab seminar

k 0/2 2 kr., podzim

• prof. RNDr. Antonín Kučera, Ph.D. - doc. RNDr. Tomáš Brázdil, Ph.D. - doc. RNDr. Vojtěch Řehák, Ph.D. - prof. RNDr. Petr Hliněný, Ph.D. - doc. Mgr. Jan Obdržálek, PhD. - RNDr. Petr Novotný, Ph.D. - Dr. rer. nat. Achim Blumensath
• Prerequisities: souhlas
  The enrollment must be approved by a teacher of a seminar group.
• Goals: By passing this course, the student will gain a profound insight into the relevant part of theoretical computer science or mathematics (depending on the selected seminar group), will be able to read and present results formulated in a given scientific literature.
• Learning outcomes: The student has a profound insight into the relevant parts of theoretical computer science or mathematics (depending on the chosen seminar group), is able to present the given specialized substance independently and solve related research problems.
• Syllabus: Team study or team research project.
  At the beginning of the semester the studied topics is selected in a common discussion.
  At regular weekly seminars a selected student (or the lecturer) explains the subject.
  At the designated seminars students refer to their progress and results, they are given feedback.
  At the final seminar an overall assessment is made.

IV125 Formela lab seminar

k 0/2 2 kr., jaro

• Dr. rer. nat. Achim Blumensath - doc. RNDr. Tomáš Brázdil, Ph.D. - prof. RNDr. Petr Hliněný, Ph.D. - prof. RNDr. Antonín Kučera, Ph.D. - doc. Mgr. Jan Obdržálek, PhD. - doc. RNDr. Vojtěch Řehák, Ph.D.
• Prerequisities: souhlas
  The enrollment must be approved by a teacher of a seminar group.
• Goals: By passing this course, the student will gain a profound insight into the relevant part of theoretical computer science or mathematics (depending on the selected seminar group), will be able to read and present results formulated in a given scientific literature.
• Learning outcomes: The student has a profound insight into the relevant parts of theoretical computer science or mathematics (depending on the chosen seminar group), is able to present the given specialized substance independently and solve related research problems.
• Syllabus: Team study or team research project.
  At the beginning of the semester the studied topics is selected in a common discussion.
  At regular weekly seminars a selected student (or the lecturer) explains the subject.
  At the designated seminars students refer to their progress and results, they are given feedback.
  At the final seminar an overall assessment is made.

IV126 Artificial Intelligence II

zk 2/0 3 kr., podzim

• doc. Mgr. Hana Rudová, Ph.D.
• Prerequisities: The course is a continuation of the PB016 Artificial Intelligence I, PB016 completion is not a prerequisite for course completion.
  It is presumed knowledge of probability theory corresponding to the course MB103 Continuous models and statistics.
• Goals: The course completes comprehensive introductory knowledge of artificial intelligence following the lecture PB016 Artificial Intelligence I. The course discusses search algorithms concentrating on metaheuristics and local search, classical planning, uncertain reasoning, and introduction into robotics oriented on robot path planning.
• Learning outcomes: The course completes comprehensive introductory knowledge of artificial intelligence following the lecture PB016 Artificial Intelligence I. It presents additional important chapters from the classic book by Russell & Norvig Artificial Intelligence: A Modern Approach (see aima.cs.berkeley.edu). Local search, planning, dealing with uncertainty, and robotics are introduced in the course.
  The graduate will be aware of base and advanced local search algorithms and will be able to solve practical problems with their help.
  The graduate will be able to work with planning problems completed by a sequence of actions to achieve the given goal.
  The graduate will gain an overview of how to work with uncertainties in the given problem and will learn to use basic procedures to include uncertainty in problem solving.
  The graduate will be aware of the base concepts from robotics and will get an understanding of the robot path planning.
• Syllabus: Local search and metaheuristics: Single-solution based search, principles, and concepts, strategies for improving local search. Population-based search, evolutionary algorithms, swarm intelligence.
  Planning: Problem representation. State space planning, forward and backward planning, domain-specific planning. Plan space planning, partial order planning.
  Uncertain knowledge and reasoning: Probabilistic reasoning, Bayesian networks, exact and approximate inference. Time and uncertainty. Utility theory, decision networks. Sequential decision problems, Markov decision processes.
  Robotics: Robot hardware, robotic perception, robot scheduling in manufacturing. Path planning in robotics, movement.

IV127 Adaptive Learning Seminar

k 0/2 2 kr., podzim

• doc. Mgr. Radek Pelánek, Ph.D.
• Goals: Students gain experience with reading and presenting research papers and they perform and present their own research and development in the area of adaptive learning.
• Learning outcomes: At the end of the course, students will be able to critically assess current research and development in the area of adaptive learning.
• Syllabus: Presentation of research papers from research areas relevant to the Adaptive learning lab - educational data mining, machine learning, cognitive psychology. Development of educational systems, analysis of educational data, presentation and discussion of results.

IV127 Adaptive Learning Seminar

k 0/2 2 kr., jaro

• doc. Mgr. Radek Pelánek, Ph.D.
• Goals: Students gain experience with reading and presenting research papers and they perform and present their own research and development in the area of adaptive learning.
• Learning outcomes: At the end of the course, students will be able to critically assess current research and development in the area of adaptive learning.
• Syllabus: Presentation of research papers from research areas relevant to the Adaptive learning lab - educational data mining, machine learning, cognitive psychology. Development of educational systems, analysis of educational data, presentation and discussion of results.

IV128 Online Communication from Social Science Perspective

z 0/2 4 kr., jaro

• prof. PhDr. David Šmahel, Ph.D.
• Goals: This seminar should introduce basic theories and research of online communication, what will help students of informatics to better understand to specifics of online communication.
• Learning outcomes: - knowledge of basic theories of online communication - knowledge of theories related to experimenting with online identity - knowledge of theories and empirical research related to trust in online information
• Syllabus: 1. Intro 2. Communication theory 3. Reliability of online data 4. Privacy in virtual world 5. Phishing 6. A methodology of online communication 7. Communication in virtual teams. 8. Addiction to online communication 9. Health and internet 10. Mediation of using internet 11. Safe online behavior 12. Research in online security 13. Conclusions

IV129 Sybila Laboratory

z 0/0 2 kr., podzim

• doc. RNDr. David Šafránek, Ph.D. - prof. RNDr. Luboš Brim, CSc.
• Prerequisities: SOUHLAS
  Applicants should 1) be able to work independently 2) have interest in long-term projects (several semesters) 3) have working knowledge of English 4) be able to work in a team. The enrollment must be approved by one of the laboratory researchers (L. Brim, D. Šafránek).
• Goals: On successful completion of the course students - will have practical experience with active research - should be able to read and understand scientific papers - should be able to employ gathered information to formulate and prove their own hypotheses within the relevant context - should be able to present the research results in English.
• Learning outcomes: After the course the student will be able:
  - to analyse and discuss pros and cons of computational methods in systems biology;
  - to contrast conceptual errors in analysed publications by employing suitable arguments;
  - to judge ideas and opinions in front of students and professionals.
• Syllabus: Sybila Laboratory is a team project focused on the development of methods and tools for the design and analysis of biological systems and their experimental application. Students meet regularly with senior researchers to discuss research problems related to their research topics. Students are expected to regularly present state-of-the-art results in the relevant fields at the laboratory seminar.

IV129 Sybila Laboratory

z 0/0 2 kr., jaro

• doc. RNDr. David Šafránek, Ph.D. - prof. RNDr. Luboš Brim, CSc.
• Prerequisities: SOUHLAS
  Applicants should 1) be able to work independently 2) have interest in long-term projects (several semesters) 3) have working knowledge of English 4) be able to work in a team. The enrollment must be approved by one of the laboratory researchers (L. Brim, D. Šafránek).
• Goals: On successful completion of the course students - will have practical experience with active research - should be able to read and understand scientific papers - should be able to employ gathered information to formulate and prove their own hypotheses within the relevant context - should be able to present the research results in English.
• Learning outcomes: After the course the student will be able:
  - to analyse and discuss pros and cons of computational methods in systems biology;
  - to contrast conceptual errors in analysed publications by employing suitable arguments;
  - to judge ideas and opinions in front of students and professionals.
• Syllabus: Sybila Laboratory is a team project focused on the development of methods and tools for the design and analysis of biological systems and their experimental application. Students meet regularly with senior researchers to discuss research problems related to their research topics. Students are expected to regularly present state-of-the-art results in the relevant fields at the laboratory seminar.

IV130 Pros and Cons of Intelligent Systems

zk 2/0 2 kr., jaro

• prof. RNDr. Jiří Zlatuška, CSc.

PB001 Introduction to Information Technologies

zk 2/0 2 kr., podzim

• prof. RNDr. Luděk Matyska, CSc. - doc. RNDr. Eva Hladká, Ph.D.
• Prerequisities: ! PB002 && ! NOW ( PB002 )
  
• Goals: To provide basic orientation in the information technology fields is the main goal of this lecture. Not only hardware and software is discussed, but the social extent is covered as well.
  The graduate will be able to understand function of simple computer systems.
  Graduate will be also able to understand and explain relationship between components of more complex computer systems.
  Graduate will be also able to analyze and explain behavior of operating systems, computer networks etc. from the user point of view.
  Graduate will be able to analyze and evaluate ethical implications of his own work.
• Learning outcomes: At the end of this course student will have basic orientation in computer and information technologies and their design. Specifically, she will understand basic principles of computer and computer systems design, she will be acquainted with principles of programming and specific constructs like interruption, synchronization, input/output. She will know basic principles of design of operating systems that are used as an example of complex computer systems; she will know what API is.
  He will also get basic overview and orientation in computer networks an computer graphics.
  The graduate will also get basic orientation in ethics and professional context and she will also be able to comment societal impacts of computer technology.
• Syllabus: Computer and communication system, role of components (architecture, operating systems, computer networks), applications.
  Social and ethical dimension of IT.
  Computer architecture, data representation, von Neumann model, basic machine organization.
  Role of operating systems, history, functionality of a typical contemporary OS.
  Design principles, efficiency, robustness, flexibility, compatibility, ...
  Influence of requirements of security, networking, graphical interfaces, ...
  OS structure (monolithic, layered, modular, micro-kernel).
  Abstraction, processes, resources, application interfaces.
  I/O devices and their management, drivers.
  Protection, system and user space, kernel.
  Networks, their history, Internet, fundamentals of network architecture, distributed systems.
  Protocols, multimedia systems, distributed computing, mobile and wireless computing.
  Basics of Human-Computer interaction, graphical systems.
  Social context of IT, Information society, New economics.
  Internet, grows, management, international issues.
  Professional and ethical responsibility, basic laws (personal data protections, digital signature, ...). Ethic codes, professional bodies, organizational's "Acceptable use policy".

PB006 Principles of Programming Languages and OOP

zk 2/0 2 kr., podzim

• doc. Mgr. Jan Obdržálek, PhD.
• Prerequisities: IB111 && PB071 && IB015
  The course is, due to its synthetic nature, intended for students with some knowledge of a modern imperative programming language (Python), some low-level language (C) and a functional programming language (Haskell).
• Goals: The goal of this course is to introduce students to the various concepts present in modern programming languages. The course also serves as an introduction to object-oriented programming.
• Learning outcomes: By the end of the course, the student will be able:
  to choose a programming language (programming paradigm) suitable for a given problem domain;
  to analyze both strong and weak aspects of a given programming language;
  to quickly obtain an in-depth understanding a of new programming language;
  understand the principles of object-oriented programming.
• Syllabus: Names, bindings, scopes. Block structure. Representing object in memory.
  Primitive and composite types. Typechecking. Lists. Pointers and references. Type derivation.
  Control flow: expressions, statements, control structures.
  Subprograms: local definitions, parameter passing, overloaded and generic functions. Coroutines.
  Abstract data types: basic concepts, encapsulation, case studies. Parameterized ADT, generics. Namespaces.
  Object oriented programming: principles, inheritance, dynamic binding.
  Exceptions: basic concepts, case studies, exceptions in functional programming languages. Event handling.

PB007 Software Engineering I

zk 2/2 3 kr., podzim

• doc. Ing. RNDr. Barbora Bühnová, Ph.D.
• Prerequisities: PB006 || NOW ( PB006 ) || PB161 || NOW ( PB161 ) || PB162 || NOW ( PB162 ) || IB114
  
• Goals: Introduction to software engineering.
• Learning outcomes: At the end of the course students should:
  know the basic steps and tasks of the IS development process;
  have detailed understanding of the techniques of requirements specification, system analysis and design, testing and maintenance;
  know the characteristics of object-oriented approach to system analysis and design;
  be able to model a medium-size IS in UML.
• Syllabus: Software development, UML Use Case diagram.
  Requirements specification, UML Activity diagram.
  System analysis and design, structured vs. object-oriented A&D.
  Object oriented analysis, UML Class diagram, Object diagram and State diagram.
  Data modelling and management, ERD.
  High-level design, UML Class diagram in design.
  Low-level design and implementation, UML Interaction diagrams.
  Architecture design, UML Package, Component and Deployment diagram.
  Testing, verification and validation.
  Operation, maintenance and system evolution.
  Software development management.
  Advanced software engineering techniques.

PB009 Principles of Computer Graphics

zk 2/1 3 kr., jaro

• doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: The knowledge of matrix calcul, linear algebra and geometry.
• Goals: The aim of the course is to give the students an overview of the basic algorithms and methods for modeling and rendering. The gained knowledge will enable the students to understand a vast range of computer graphics tasks, including their mathematical background. Within the seminars, practical experience will be gained by programming the selected algorithms.
• Learning outcomes: After finishing the course, the students
  - will orient themselves in a broad spectrum of computer graphics problems;
  - will understand the underlying math foundations and programming issues as well;
  - gain practical knowledge in programming the algorithms.
• Syllabus: Introduction to computer graphics, types of displays.
  Polygon filling, basic graphical primitive and raster algorithms, line rasterization.
  Basic operations on raster images.
  Color, color models, color perception.
  Introduction to textures.
  Basic lighting models, texture mapping.
  Linear transformations, projection.
  Clipping in a 2D plane.
  Interpolating and free-form curves and surfaces.
  Models and modeling 3D objects.
  Visibility in object space.
  Shading and rendering.
  Global illumination, ray tracing, radiosity.

PB016 Artificial Intelligence I

zk 2/2 3 kr., podzim

• doc. RNDr. Aleš Horák, Ph.D. - doc. RNDr. Lubomír Popelínský, Ph.D.
• Goals: Introduction to problem solving in the area of artificial intelligence. The main aim of the course is to provide information about fundamental algorithms used in AI.
• Learning outcomes: After studying the course, the students will be able to:
  - identify and summarize tasks related to the field of artificial intelligence;
  - compare and describe basic search space algorithms;
  - compare and describe main aspects of logical systems;
  - understand different approaches to machine learning;
  - compare and describe different ways of knowledge representation and reasoning;
  - present basic approaches to computer processing of natural languages.
• Syllabus: Artificial intelligence, Turing test
  Solving problems by searching.
  Heuristics, Best-first search, A* search.
  Problem decomposition, AND/OR graphs.
  Constraint Satisfaction Problems.
  Games and basic game strategies.
  Logic agents, propositional logic, satisfiability.
  Truth and provability. Axiomatic systems.
  First order predicate logic, intensional logic.
  Resolution in propositional and predicate logic. Introduction to logic programming.
  Modal logic. Multivalued logic.
  Knowledge representation and reasoning, reasoning with uncertainty.
  Learning, decision trees, neural networks.
  Natural language processing.

PB029 Electronic Document Preparation

zk 2/1 3 kr., podzim

• doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: No strict prerequisites are set. Knowledge of basic algorithmic techniques and attention to detail is a plus. Students would benefit from basic knowledge of Unix scripting environment (e.g. from attending PV004 UNIX).
• Goals: Basic principles, algorithms and techniques used in electronic publishing are taught. Point of view is narrowed with respect to the creation of sizable, structured, technical documents like theses or dissertation, and presentations -- it is ideal to enroll before writing first thesis (in TeX). Web publishing is also covered.
• Learning outcomes: At the end of the course students should be able to apply basic principles, algorithms and technologies of (team) document preparation and production, namely as an author of technical documents (thesis, course presentation materials, program documentation, web presentation or for quality database publication). Students will use typesetting system TeX suite of programs.
  Students will be able to pick up and work with appropriate tools and software packages used in the electronic documents' development cycle and preparation of above specified document types.
• Syllabus: From author to the reader: document preparation cycle.
  Markup Logical structure of a document; markup languages. LaTeX as a markup language. HTML5, SGML, HTML, XML. Document grammars. DTD, XML Schema.
  Design. Principles of book design. Specifics of web design. CSS, XSL(T).
  Typesetting. Typesetting, typography. Basic principles, rules for Czech and English. Terminology.
  Typefaces. Classification of type. Formats, rasterization of fonts. Type 1, Multiple master fonts.
  Typesetting systems. TeX -- principles, philosophy, macro programming. Microtypography.
  Algorithms of line and page breaking, hyphenation.
  Page description languages. Post-Script. Bézier curves.
  Print and Distribution. Output devices and their characteristics. Phototypesetting, printing and binding.
  Hypertext, hypertext systems. Formats for electronic delivery. Portable Document Format, technology Adobe Acrobat.
  Parallel WWW and paper publication. Database publishing. Document format conversion. Specifics of presentation preparation.

PB050 Modelling and Prediction in Systems Biology

zk 1/1 2 kr., podzim

• doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: This is an interdisciplinary course that extends the knowledge of bachelor students of all study branches. The course is especially recommended for students of Bioinformatics.
• Goals: At the end of the course, students will be able to:
  understand basic principles of quantitative modeling,
  understand dynamic computational models of complex systems in the domain of biological processes;
  apply abstract computer-scientific thinking to modeling and analysis of complex systems with special focus to biological systems;
  practically use state-of-the-art modeling and analysis software tools;
  model and analyze dynamic properties of complex interaction networks.
• Learning outcomes: At the end of the course, students will be able to:
  describe basic principles of quantitative modeling,
  constract dynamic computational models of complex systems in the domain of biological processes;
  apply abstract computer-scientific thinking to modeling and analysis of complex systems with special focus to biological systems;
  use state-of-the-art modeling and analysis software tools.
• Syllabus: History and scope of systems biology.
  Basic notions: living organism as a system with precisely given structure and functionality, in silico model, abstraction, simulation and prediction, model validation.
  Specification of a biological model: biological networks and pathways, languages SBML and SBGN.
  Emergent properties of systems dynamics, their specification and encoding.
  Modeling and simulation of biological systems dynamics: hypotheses prediction.
  Modeling of Escherichia coli bacteria: genetic regulatory network, models of locomotion organ synthesis and chemotaxis, nutritional stress response models.
  Notion of stochasticity in biological dynamics, basic principles of stochastic models, chemical master equation, Monte Carlo simulation.
  Model parameters, robustness and parameter sensitivity.

PB051 Computational methods in Bioinformatics and Systems Biology

zk 1/1 2 kr., jaro

• Ing. Matej Lexa, Ph.D. - doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: Knowledge of elementary molecular biology and basic problems in bioinformatics and systems biology is expected. Previous undertaking of courses IV107, PA054 and PB050 is welcome, but not required formally.
• Goals: At the end of the course students should be able to: select appropriate methods for a given problem; obtain and prepare necessary data; analyse the data (using their own program or publically available solutions)
• Learning outcomes: At the end of the course students should be able to:
  - select appropriate computational methods for a given problem;
  - analyse selected types of experimental data;
  - apply software tools to selected problems of data processing;
  - construct and modify qualitative models of biological networks.
• Syllabus: The course will be divided into two parts, each will cover 1-2 methods:
  Bioinformatics:
  operations on genomes
  using Markov models
  Systems biology:
  static analysis of biological networks; Cytoscape, MAVisto tools
  genetic regulatory networks reconstruction; Genomica, ARACNE tools
  data integration

PB069 Desktop Application Development in C#/.NET

zk 2/2 3 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Prerequisities: Knowledge of programming, C# programming language that is adequate to the course PV178 Introduction to Development in C#/.NET, and MS Windows operating system (on a user level).
• Goals: The course Desktop Application Development in C#/.NET introduces students to the basic techniques used for development of applications aimed for the environment of MS Windows operating systems. The course targets development of simple applications together with their graphical user interface, using C# programming language, MS .NET platform, Windows Forms programming interface, and Windows Presentation Foundation. The topics are taught and demonstrated in Microsoft Visual Studio.
• Learning outcomes: At the end of the course, the student will:
  know the principles and rules of event-driven programming;
  be familiar with the MS Visual Studio environment, Windows Forms interface, and Windows Presentation Foundation;
  know the rules of designing graphical user interfaces of applications;
  be able to use the basic classes of the Windows Forms interface and the Windows Presentation Foundation;
  be able to develop applications for the MS Windows environment together with their user interface.
• Syllabus: Event driven programming. The model of a MS Windows program.
  Integrated development environment MS Visual Studio, simple applications creation.
  Usage of Windows Forms basic classes and work with them.
  Processing of events coming from the keyboard and mouse.
  Dialog boxes and their handling.
  Programming with graphics.
  Rules for the design of graphical user interface of applications.
  Basic standard dialogs.
  Programming with the clipboard, support of drag & drop, programming with Windows registry.
  Support of multi-threading in applications.
  Printing from the environment of MS Windows.
  Programming with Win32 API.
  Introduction to Windows Presentation Foundation.
  Design of applications using Windows Presentation Foundation.

PB071 Principles of low-level programming

zk 2/2 4 kr., jaro

• doc. RNDr. Petr Švenda, Ph.D.
• Prerequisities: Students are expected to have the basic knowledge of algorithmization in Python or another procedural language. Students are also required to have user experience with Unix/Linux OS, as homework is submitted and tested on a Unix/Linux server.
• Goals: At the end of the course students should be able to:
  Understand and use basic C syntax according to ANSI and ISO/IEC norms.
  Decompose given problem and perform practical implementation.
  Use modern development tools (IDE, debugger, version control...).
  Understand basic C functions for POSIX system.
  Annotate source code with possibility to automatically generate documentation. Understand and practically use documentation for existing functions.
  Use and follow programming best practices.
  Compile programs both under Unix/Linux and Windows.
• Learning outcomes: After a course completion, the student will be able to:
  - write non-trivial programs in C language;
  - use basic development tools including IDE, debugger, versioning system and dynamic analysis of memory use;
  - understand code execution on the level of CPU and memory;
  - use dynamic allocation and apply correct deallocation where necessary;
  - write programs with an application of good programming practices;
• Syllabus: Historical background of the C language. Its relation to the Unix OS.
  C compilers under Unix and MS-DOS/MS-Windows, integrated development environment, debugger, version control. Good programming practices, testing.
  Data types, constants, declarations, expressions. Assignment expressions and statements.
  Basic program structure. Preprocessor statements. Comments. Control structures. Relational expressions. Elementary I/O operations.
  Arrays and pointers. Functions. Calling by value, passing arguments by pointer.
  User defined data types. Dynamic memory allocation.
  I/O in details. Using files. Wide characters.
  Strings and string manipulation. Standard C library according to ANSI and ISO/IEC standards. Calling Unix core services. Further Unix libraries for C. POSIX C Library. Implementation on Windows.
  Safe and defensive programming.
  Automated and manual testing.

PB095 Introduction to Speech Processing

zk 2/0 2 kr., podzim

• Mgr. Luděk Bártek, Ph.D.
• Goals: The course provides an introduction to speech processing oriented to human-computer interaction, i.e. especially to speech synthesis, speech recognition and dialogue systems. Main objectives can be summarized as follows: To understand the basic principles of sound and speech production and perception; To understand basic principles of speech regognition,synthesis and dialogue systems; To obtain an introductory overview in the field.
• Learning outcomes: Student will be able after finishing the course to describe and explain the basic terms, methods and standards in following areas:
• physical acoustics
• physiological acoustics, especially the processes of forming and understanding the human speech
• phonetics and phonology
• signal digitization and basic signal processing in time and frequency domains
• isolated words and commands recognition
• continues speech recognition
• time and frequency domain text-to-speech synthesis
• relation of prosody a emotions to tts and speech recognition
• dialogue communication
• dialogue systems
• user modeling in dialogue systems
• dialogue systems applicaiton.
• Syllabus: Introduction
  Brief history
  State of the art
  Physical and physiological acoustics
  Creation and perception of human speech
  Phonetics a phonology
  Signal processing
  Principles of speech synthesis
  Speech segments and concantenative speech synthesis
  Prosody, emotions
  Principles of speech recognition
  Statistical approaches
  Modelling by means of HMM
  Language modelling
  Human-human and human-computer communication
  Dialogue
  Dialogue Systems - Voice Browser Activity Standards (VoiceXML, SRGS, SISR, etc.)
  User modelling
  Dialogue systems and applications

PB106 Corpus Linguistic Project I

z 0/2 2 kr., podzim

• doc. Mgr. Pavel Rychlý, Ph.D.
• Goals: The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of corpus linguistics and practical checking of this knowledge by working on the project. The popularisation of corpus linguistics and other areas of language engineering is one of the main goals of Natural Language Processing Laboratory at the Faculty of Informatics.
  Fundamental information about the Natural Language Processing Laboratory and corpus linguistics in general can be found on http://www.fi.muni.cz/nlp/.
• Learning outcomes: Student will be able to: create a text corpus from different sources; use automatic tools for corpus annotation; evaluate accuracy of automatic tools; present evaluation results.
• Syllabus: theme introduction: text corpora, parallel corpora, annotation, statistics, user interfaces
  project selection
  work on a project
  presentation of project results and discussion

PB130 Introduction to Digital Image Processing

zk 2/1 3 kr., podzim

• doc. RNDr. Petr Matula, Ph.D.
• Prerequisities: ! PV131
  Knowledge of high-school mathematics and understanding and design of simple algorithms is supposed.
• Goals: The objective of the course is to introduce students to the area of digital image processing in order to get necessary background for studying other courses from the area.
• Learning outcomes: At the end of the course a student should: know the basic terminology related to digital image processing; know about the typical problems from digital image processing; understand the principle of simple algorithms for image processing and know how to use them. The course is intended as an introduction to digital image processing.
• Syllabus: Human vision, image acquisition and basic image computer representations.
  Color images.
  Point transforms. Histogram.
  Linear image filtering. Convolution.
  Non-linear filters.
  Mathematical morphology.
  Edge detection. Gradient.
  Regions in binary images and their description.
  Image segmentation.
  Applications of digital image processing.

PB138 Modern Markup Languages and Their Applications

zk 2/1 3 kr., jaro

• doc. RNDr. Tomáš Pitner, Ph.D. - Mgr. Luděk Bártek, Ph.D. - RNDr. Adam Rambousek, Ph.D. - Ing. Lukáš Grolig
• Prerequisities: Basic knowledge of formal languages, as well as some experience in OO programming, such as in Java, C++, C# or ECMAScript, and databases is required. Moreover, basic orientation in a markup language (HTML) and Internet services is needed, too.
• Goals: The subject acquaints with basic standards and principles of working with technologies of modern markup languages mainly based on XML, JSON and Yaml. Upon successful completion of this course, students will create modern applications written in TypeScript using React and modern markup languages that retrieve data from the backend using REST interfaces or GraphQL query language. At the same time, it can deploy its applications in the cloud using Kubernetes containers.
• Learning outcomes: Students will be able to:
  - explain the advantages, disadvantages and purpose of tagged data and documents;
  - actively use terminology of markup languages
  - choose the appropriate markup language for the application
  - actively use XML
  - Describe the characteristics of Internet technologies such as HTML 5, JavaScript, React, JSON, GraphQL and other modern web standards
  - Describe the principle of Single Page applications
  - describe the meaning of containers, their use in developing and hosting applications in the cloud
• Syllabus: XML Structure and terminology of tagged documents. Standard family XML standards; Standards of XML data analysis and processing. Document object model, event-driven processing; Navigation and querying in XML data. XPath
  Yaml Syntax Yaml; Yaml application for CII configuration; Work with Docker containers and Kubernetes
  Basics of modern Javascript applications; HTML document; Node ecosystem, NPM dependency management
  Introduction to React, JSX / TSX language; Definition of components and their composition; Life cycle of components; Application status; Work with lists; Forms
  JSON Syntax; Data types in JSON; Field and object representation; REST interface principles
  GraphQL Introduction to GraphQL; Schemes; Queries; Mutation; Type system; Validation

PB150 Computer-Systems Architectures

k 2/0 2 kr., podzim

• doc. Ing. Michal Brandejs, CSc.
• Prerequisities: ! PB151 && ! NOW ( PB151 )
  
• Goals: At the end of the course student should be able to understand and explain a general technical principles about computer systems operation.
• Learning outcomes: At the end of this course the student will be able to understand basic principles of digital computers; understand the design of numerical systems used in computer technology and convert numbers between systems; will understand the principles of storing information, coding and storing texts. The student will understand the principles of the elementary processor and its programming at the lowest level.
• Syllabus: Terms, history, computer generations, categories.
  Numeral systems, differences between systems, integer, arithmetics.
  Codes, internal, external, ECC.
  Electronic circuits, memories: parameters, architecture.
  Processor, programming, microprogramming.
  Architectures: RISC/CISC, cache memories.

PB151 Computer Systems

zk 3/0 3 kr., podzim

• doc. Ing. Michal Brandejs, CSc.
• Prerequisities: ! NOW ( PB150 )
  
• Goals: At the end of the course student should be able to understand and explain a general technical principles about computer systems operation.
• Learning outcomes: At the end of this course the student will be able to understand basic principles of digital computers; understand the design of numerical systems used in computer technology and convert numbers between systems; will understand the principles of storing information, coding and storing texts. The student will understand the principles of the elementary processor and its programming at the lowest level. Student general principles compare with a specific implementation on Intel x86 processors and will be able to understand the implemented technologies of paging, caching and some others.
• Syllabus: Terms, history, computer generations, categories.
  Numeral systems, differences between systems, integer, arithmetics.
  Codes, internal, external, ECC.
  Electronic circuits, memories: parameters, architecture.
  Processor, programming, microprogramming.
  Processor architecture, memory addresses, operational modes, register structures.
  Architectures: RISC/CISC, cache memories.
  IEEE 754.
  I/O devices and its connections.

PB152 Operating Systems

zk 2/0 2 kr., jaro

• RNDr. Petr Ročkai, Ph.D.
• Prerequisities: ! PB153 &&! NOW ( PB153 )
  Understanding of computer system architectures to the extent covered in the subject PB150 or PB151.
• Goals: The subject gives a high-level overview of operating systems and their architectures. Students will learn about the basic components that make up an operating system and how they fit together. Students should also gain a basic understanding of design considerations and internal working of the individual components. Finally, the subject will cover services that the OS provides to user-level programs and to users directly.
• Learning outcomes: By the end of the course, the student should be able to: - name and describe what makes up an operating system
  - explain how the individual components work
  - use operating system services both as a user and a programmer
  - describe how resource sharing works: memory, cpu, etc.
• Syllabus: 1. Anatomy of an OS
  2. System Libraries and APIs
  3. The Kernel
  4. File Systems
  5. Basic Resources and Multiplexing
  6. Concurrency and Locking
  7. Device Drivers
  8. Network Stack
  9. Command Interpreters & User Interfaces
  10. Users and Permissions
  11. Virtualisation & Containers
  12. Special-Purpose Operating Systems
  13. Review

PB152cv Operating Systems - practicals

z 0/2 2 kr., jaro

• RNDr. Petr Ročkai, Ph.D.
• Prerequisities: PB153 || PB152 || NOW ( PB152 )
  It is recommended that the course is taken at the same time as PB071 Principles of low-level programming.
• Goals: The course extends the material covered in PB152 Operating Systems, particularly in the form of practical exercises. The main goal is to learn how to use operating system services when writing programs.
• Learning outcomes: The student, after completing this course, should know how to:
  - automate simple tasks by writing scripts
  - use the basic POSIX interfaces in C programs
  - work with files and directories
  - program a simple multi-process service
  - create an operating system image in a virtual machine
• Syllabus: 1. command interpreter
  2. compiler, linker, creating programs
  3. scripts 1, make
  4. working with files
  5. processes, fork
  6. interprocess communication
  7. threads
  8. networking
  9. automation, scripts 2
  10. permissions
  11. virtualisation
  12. creating an OS image

PB153 Operating Systems and their Interfaces

zk 2/0 2 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: ! PB152 &&! NOW ( PB152 )
  Basic knowledge of architectures and principles of computing systems. (at least on the level of PB150 or PB151).
• Goals: The course introduces basics of operating systems ant heir interfaces.
• Learning outcomes: At the end of the course students will be able to understand and explain the basics of operating systems architectures, processes, memory and I/O management, filesystems. Based on the acquired knowledge student will be able to use services (API) offered by common OS types (Unix, Linux, Windows).
• Syllabus: Operating systems architectures, kernel, interfaces, services
  Process management, processes, threads, scheduling, process synchronization
  Memory management
  IO Management, File systems
  Interfaces and services of Unix, Linux and Windows.

PB154 Database Systems

zk 2/1 3 kr., podzim

• prof. Ing. Pavel Zezula, CSc.
• Prerequisities: Ability to understend a computer-specialized English text.
• Goals: The goal of the course is to teach students principles of database systems.
• Learning outcomes: On successful completion of the course the student will be able:
  to formulate reasons for using database systems;
  to understand basic principles of database systems;
  to describe ways of indexing data;
  to design a database schema;
  to create queries for retrieving data.
• Syllabus: Introduction, terminology
  Entity-relationship model
  Relational model
  Query language SQL
  Integrity constraints
  Relational database design
  Storage and file structures
  Indexing and hashing
  Query processing
  Transaction management
  New trends in database systems

PB156 Computer Networks

zk 2/0 2 kr., jaro

• doc. RNDr. Eva Hladká, Ph.D.
• Goals: The main goal of this course is to provide the students with basic understanding of behaviour and principles of computer networks, with special emphasis on network architecture and protocols forming contemporary Internet. The course mainly focuses on general principles rather than the technologies currently used.
• Learning outcomes: Graduate will understand the standardized network architecture model (ISO/OSI model) and its modification used in contemporary computer networks (TCP/IP model).
  Graduate will have a good orientation in basic network protocols used in contemporary computer networks.
  Graduate will understand basic principles of addressing, routing and switching in IP networks, he or she will be able to design a simple computer network.
  Graduate will understand the behavior of UDP and TCP protocols in IP networks.
  Graduate will understand requirements of individual applications and application classes, which they have on the computer network and its quality. He or she will also obtain a basic orientation in parameters defining quality of service.
• Syllabus: Computer networks' architecture, connection-oriented and connectionless networks, network models (ISO/OSI, TCP/IP) and network examples. Internet as a network of networks. Network protocols, standardization.
  Overview of physical and data link layers' services -- signals, transport media, media access control, building L2 networks.
  Network layer -- services, interaction with L2 layer, addressing, Internet protocols IPv4 and IPv6, local (LAN) and wide area (WAN) networks. Routing mechanisms, common routing protocols (RIP, OSPF, BGP), autonomous systems, multicast.
  Transport layer -- services, UDP and TCP protocols, mechanisms of ensuring transmissions' reliability. Quality of service.
  Application layer -- kinds of network applications (client-server vs. peer-to-peer model), applications' requirements on computer networks. Examples of selected applications (e.g., DNS, HTTP/WWW, multimedia applications).

PB156cv Computer Networks - practicals

z 0/2 2 kr., jaro

• doc. RNDr. Eva Hladká, Ph.D.
• Prerequisities: Runs in parallel with PB156
• Goals: The goal of the exercise si to give students enrolled to the PB156 Computer Networks course an opportunity to get direct hands-on experience with network protocols and their use.
• Learning outcomes: The primary output follows those of PB156, but extending the presentations with direct use of the presented materials. The graduates will get practical experience with building simply networks, analysis the traffic, understanding most of the protocols presented in lectures through actually building them and-or following them over the built network.
• Syllabus: Introduction, getting acquainted with Wireshark, the packet sniffing suite. Practical experience with HTTP, differences between protocols, simple get, put, retrieval of longer protocols, simple authentication DNS, dns lookup, ipconfig, dns tracing TCP protocol, analysis of TCP packets, TCP congestion control UDP protocol, analysis of UDP packets IP protocol, analysis of IP packets, packet fragmentation, ICMP Ethernet and ARP, Ethernet frames, ARP caching DHCP protocol, packets analysis, setting up a DHCP server (The structure is inspired and to large extent follows the Wireshark Laboratory of Kurose and Ross)

PB161 C++ Programming

zk 2/2 3 kr., jaro

• RNDr. Petr Ročkai, Ph.D. - Mgr. Lukáš Korenčik - Mgr. Jan Mrázek - RNDr. Lukáš Ručka - RNDr. Vladimír Štill
• Prerequisities: PB071
  Students are also required to have user experience with Unix OS or similar, as homework is submitted and tested on a Unix server.
• Goals: The goals of the course are to make the students familiar with the C++ programming language (as defined by ISO C++14) and the object-oriented programming principles (as implemented by C++). The course focuses mainly on using the standard library, efficient design of own data structures (classes), the principles of resource management, and the basic principles of object-oriented design.
• Learning outcomes: After finishing this course, a student should be able to:
  - write C++ programs utilizing the tools of modern C++ (as defined by ISO C++14);
  - use a significant part of the standard C++ library;
  - create user-defined data types (classes) in C++;
  - understand the value semantics of C++ and explain the difference between this semantics and other popular languages' semantics;
  - understand the principles of object-oriented programming;
  - design simple object-oriented architectures and implement them;
  - use exceptions in an efficient and reasonable way;
  - use modern development tools (IDE, debugger, version control, build automation tools, testing frameworks...);
  - follow best practices guidelines for C++ programming.
• Syllabus: Basic features of C++ (with respect to C). Standards, compilers.
  Value and reference semantics of C++.
  Basic principles of object oriented programming (OOP). Object programming methodologies.
  User defined data types. Classes in C++. Class components.
  OOP in C++. Encapsulation, Inheritance, Polymorphism.
  Dynamic memory allocation. Dynamic memory management. Automatic and class pointers.
  Input and output in C++.
  Exception handling. Defensive programming.
  Templates. Standard C++ library and standard template library. Libraries for numeric computing.
  Application of object oriented design and design patterns in C++.
  Other OOP languages. Java and C# as compared to C++.

PB162 Java

zk 2/2 3 kr., jaro

• doc. RNDr. Tomáš Pitner, Ph.D. - RNDr. Radek Ošlejšek, Ph.D.
• Prerequisities: Command of a procedural programming language (Python, C) in the extent of the IB001 Introduction to Programming using C, IB111 Foundations of Programming, or IB113 Introduction to Programming and Algorithms.
• Goals: During this course, students:
  gain the basic knowledge of object oriented programming in Java;
  become familiar with the basic Java and OO terminology, as well as necessary language syntax and semantics rules;
  be able to analyze, design and implement simple software solutions with the appropriate tools.
• Learning outcomes: At the end of the course students should be able to:
  explain and use principles of object paradigm;
  use basic principles of object-oriented design for coding;
  create programs on Java SE platform;
  use development tools efficiently, e.g. IDE, unit tests, git, etc.;
• Syllabus: Introduction to Java - principles, history. Java development lifecycle, basic development tools.
  Basic concepts and terminology of object-oriented programming - class, instance (object), variable, method. Encapsulation.
  Cooperation and communication among objects.
  Interfaces, specification, implementation.
  Basic programmer's conventions - coding style, naming, documentary comment, API documentation.
  Unit testing with junit.
  Inheritance, polymorphism. Class hierarchy. Architecture of Java programs - methods, classes, packages.
  Abstract classes. Access modifiers.
  Basic program constructs. Primitive datatypes, object types and arrays.
  Exceptions. Built-in exceptions, design of custom exceptions.
  Java containers.
  Java I/O.
  Basic design patterns.

PB168 Introduction to DB and IS

zk 2/2 3 kr., podzim

• doc. RNDr. Vlastislav Dohnal, Ph.D. - RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: ! PB154 && ! NOW ( PB154 )
  Basic knowledge of technical English
• Goals: The aim of the course is to introduce principles of information and database systems to the students. In detail, issues of creating information systems that use database systems will be tackled. Especially, we focus on the topics of software engineering, database design and data modeling, querying and other functionality including analytical tools. The aim of one-hour seminars is to exercise selected phenomena in practice. The students will get an idea about the overall problem of design and development of information systems and its individual stages. The students will learn principles of database systems from the theoretical and practical points of view. The students will be able to use a relational database system, store and query its data.
• Learning outcomes: Student will be able to:
  - Explain basic principles and procedures in designing software;
  - Apply these procedures to create a model of smaller information system;
  - Explain the principles of relational database management systems;
  - Design and implement relational model for data storage in the information system;
  - Formulate basic SQL statements (data updates and querying in particular);
  - Be familiar with the issues of analysis and design of data-oriented information systems.
• Syllabus: Introduction to information systems. What is an information system, what is its purpose, what is its task and how it is useful. The common structure and components of an information systems, examples. Modern information systems.
  Introduction to database systems. What is a database management system, what is its task and use, examples. Data abstraction, models, examples.
  Architecture of database systems. Design of database, querying. Query languages. Architecture of database. Users of database.
  Entity-relationship model. Attributes, entity sets. Relationships, cardinality. Definition of key, primary key.
  Relational model. Relation, attributes, relationships. Transition to/from entity-relationship model. Referential integrity.
  Database design. Functional dependencies. Normal forms. Decomposition.
  SQL query language. Introduction, basic statements. Select, joins, aggregation functions. Database updates and deletions. Data definition, views.
  Query processing. Basic principles, examples. Indexing. Introduction to query optimization. Transactions. Properties of transaction processing.
  Analytical tools. OLAP – Online Analytical Processing. Data mining. Applications of databases.
  Specifics of database systems. Technology of accessing databases. Geographical information systems. Multidimensional databases. Temporal databases.
  Design and development of information systems. Life-cycle of information system. Analysis, design of systems. Structured analysis. Data Flow Diagram, mini-specification.
  Use case diagram. Sequence diagram. Class diagram.
  Principles of structured analysis based on YMSA and SSADM. Functional decomposition. Balancing functional and data models.

PB170 Seminar on Digital System Design

k 0/2 2 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D.
• Goals: At the end of the course students should be able to: understand the main concepts of digital system design (combinational and sequential circuits); know the realization of basic design (adders, counters, state automata); create and simulate the simple design.
• Learning outcomes: At the end of the course, students will be able to:
  formally describe a logic circuit composed of combinational or sequential circuits;
  design a simple digital system;
  simulate the behavior of digital circuits;
  the basic design of logic circuits in HDL Verilog
• Syllabus: Fundamentals of digital systems: description of a logic circuit, design methods.
  Basic entities: primitives (gates), combinatorial circuits, sequential circuits.
  Practical exercises with tools like Hades and Quartus.
  A short introduction into HDL, Verilog.

PB171 Seminar on Digital System Architecture

k 0/2 2 kr., jaro

• RNDr. Zdeněk Matěj, Ph.D. - prof. Ing. Václav Přenosil, CSc.
• Goals: The main objectives of the seminar are to verify the knowledge acquired during the Digital computer architecture course. The students will learn about the structure and the design of systems for selected microcomputers or FPGA, they will learn to program them and at the end of the semester, they will create their own project. The lessons will be held in the EmLab - A415.
• Learning outcomes: At the end of the course, students will be able to:
  practically design a digital system;
  program using a language assembler and C designed digital system;
  to practically assemble and integrate a digital system.
• Syllabus: Architecture of 8-bit controllers (PIC12 family).
  Assembly language for target platform.
  General purpose I/O.
  Timers and interrupt handling.
  EEPROM handling.
  Applications of the analog-digital converter.
  C language compiler for 8-bit platforms.
  Using C language for target platform-
  Controlling shift register.
  Bus drivers: UART, SPI, I2C.
  Advanced peripherals.
  Semestral project.

PB172 Systems Biology Seminar

k 0/2 2 kr., podzim

• doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: souhlas
  The seminar is focused on studying and presentation of selected scientific articles/book chapters in the field of computational systems biology. Students are assumed to understand elementary notions from biology and chemistry (grammar school level), to know basic principles of the systems biology paradigm, and to be interested in deeper understanding of the field. Previous successful studying of PB050 is welcome.
• Goals: At the end of the course students should be able to: understand key results of computational systems biology; work with a scientific paper; extract the information from literature; prepare and give an oral presentation.
• Learning outcomes: At the end of the course students should be able to:
  - analyse a scientific paper;
  - combine and infer the information from scientific literature;
  - discuss pros and cons of computational methods in systems biology;
  - contrast conceptual errors in analysed publications by employing suitable arguments.
• Syllabus:
• Overview of elementary notions and paradigms
• Selection of seminar topics (papers) and explanation of their significance
• Studying of the selected topics
• Presentation and discussion

PB172 Systems Biology Seminar

k 0/2 2 kr., jaro

• doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: souhlas
  The seminar is focused on studying and presentation of selected scientific articles/book chapters in the field of computational systems biology. Students are assumed to understand elementary notions from biology and chemistry (grammar school level), to know basic principles of the systems biology paradigm, and to be interested in deeper understanding of the field. Previous successful studying of PB050 is welcome.
• Goals: At the end of the course students should be able to: understand key results of computational systems biology; work with a scientific paper; extract the information from literature; prepare and give an oral presentation.
• Learning outcomes: At the end of the course students should be able to:
  - analyse a scientific paper;
  - combine and infer the information from scientific literature;
  - discuss pros and cons of computational methods in systems biology;
  - contrast conceptual errors in analysed publications by employing suitable arguments.
• Syllabus: Overview of elementary notions and paradigms.
  Selection of seminar topics (papers) and explanation of their significance.
  Studying of the selected topics.
  Presentation and discussion.

PB173 Domain specific development in C/C++

k 0/2 2 kr., podzim

• RNDr. Petr Ročkai, Ph.D.
• Prerequisities: PB071 || SOUHLAS
  A basic knowledge of C or C++ programming language and user-level knowledge of operating system (Unix or Windows) relevant to chosen thematic group is required. Absolved PB071 or teacher's approval is mandatory requirement for enrollment.
• Goals: At the end of the course students should be able to: use modern development tools (IDE, debugger, version control...); follow and use good programming practices; orient in real-world programming problems in area of student focus; create maintainable and extensible applications; find and remove bugs in programs by debugging and prevent its occurrence by systematic testing; correctly and effectively work with memory and large data sets; optimize application usage of available system resources;
• Syllabus: Each seminar group has its own, domain-specific syllabus. The focus of the subject is practical programming and related skills -- version controll, debugging, testing and so on.

PB173 Domain specific development in C/C++

k 0/2 2 kr., jaro

• RNDr. Petr Ročkai, Ph.D.
• Prerequisities: PB071 || SOUHLAS
  A basic knowledge of C or C++ programming language and user-level knowledge of operating system (Unix or Windows) relevant to chosen thematic group is required. Absolved PB071 or teacher's approval is mandatory requirement for enrollment.
• Goals: Enhance the capability of programming in C++ based on development in particular selected application domain.
• Learning outcomes: At the end of the course students should be able to: use modern development tools (IDE, debugger, version control...); follow and use good programming practices; orient in real-world programming problems in area of student focus; create maintainable and extensible applications; find and remove bugs in programs by debugging and prevent its occurrence by systematic testing; correctly and effectively work with memory and large data sets; optimize application usage of available system resources;
• Syllabus: Individual thematic groups (list is available in Teacher's information area) have common themes, but use practical problems from their own areas to demonstrate and practice it. Basic covered topics are:
  Introduction to area of particular thematic group
  Lifecycle of created application
  Code maintainability
  Debugging
  Work with memory
  Work with large data sets
  Systematic testing: integration and unit testing
  Robust error and exception handling
  Performance and resource optimization
  Application usability

PB175 Project managment and project

z 1/0 5 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: PB007 && PB006
  PB006 and PB007
• Goals: The course aim is to make students experience a real work on a specified complex software, where student's primary task is to program (code) a specified functionality. She will also be responsible for the integration of the programming results into the production version of the software involved
• Learning outcomes: After successful completion student will be able - to understand a complex project specification and orient in a complex code - to program and test (validate) specified function in accordance with the project specification - to integrate results (code) into a production version of the software involved - to document and pass over results of her work in a form that allows taking over by another team member (developer of the same software product)
• Syllabus: Time steps: - Selection of the project from a provided list or accepted student's project specification proposal - Individual (or team) work on the project - Regular consultations with the technical supervisor - Regular consultation with a faculty supervisor (assigned whem the technical supervisor is not a faculty] - Final project report (text and code), formally accepted by the teacher

PA008 Compiler Construction

zk 3/0 3 kr., podzim

• prof. RNDr. Mojmír Křetínský, CSc.
• Prerequisities: Finite automata and regular languages (see IB005); pushdown automata and context-free languages, especially the parsing methods of deterministic context-free languages (LL and LR techniques) - see IA006.
• Goals: At the end of the course students should be able to understand and explain principles, methods, and techniques used in design and implementation of compilers programming languages and the related systems based on analysis of an input text and synthesis of the corresponding output. Students should be able make reasoned decisions about design of these systems. Based on acquired knowledge, students should employ principles and techniques of compiler writing and program analysis in related areas of computer science and system desing.
• Learning outcomes: On successful completion of the course students will be able to:
  1. Specify and analyse the lexical, syntactic and semantic structures of language features and separate the lexical, syntactic and semantic analyses into phases for a compiler.
  2. Implement a scanner, parser, and semantic analyser with/without the aid of automatic SW tools.
  3. Write an intermediate (IR) code generator. Turn IR code into machine code. Describe techniques for intermediate code optimisation.
• Syllabus: Tasks of compiling, phases of a compiler, compiler structure.
  The role of lexical analysis. Structure, modules and interfaces. Construction.
  Parsing. The role of parser, interfaces and imlementation.
  Attribute grammars (AG) and syntax directed translation. Description of language properties via AGs.
  Semantic analysis, its tasks and implementation. Name and scope analysis, type checking.
  Run-time enviroments, storage organization and allocation, stack and heap.
  One-pass and multi-pass compiling. Intermediate code generation
  Techniques for code generation. register allocation.
  Error recovery.
  Local optimization. Flow analyses, global optimization.
  Compiler generators, techniques and tools.

PA010 Intermediate Computer Graphics

zk 2/0 3 kr., podzim

• doc. RNDr. Barbora Kozlíková, Ph.D. - prof. Ing. Jiří Sochor, CSc.
• Prerequisities: Basic algebra and geometry. Computer graphics fundamentals.
• Goals: Lectures cover classical and the most important fields of interest in computer graphics and current research results. Students should gain the purview of the critical issues and research trends in computer graphics field.
• Learning outcomes: At the end of the course students
  - will understand the theoretical concepts of modern computer graphics;
  - will be able to judge and evaluate the research and development trends in the field;
  - will be able to asses the complexity of computer graphics algorithms;
  - will be able to design complex graphics systems in various application areas.
• Syllabus: Polygon and Triangular meshes: problems, related tasks, filtering and re-meshing, simplification and approximation
  Subdivision surfaces
  Advanced modeling techniques: global and local deformations, implicit modeling
  Volume data visualization: isosurfaces
  Signal sampling and reconstruction
  Textures: mapping, filtering, synthesis
  Image transformations, warping, and morphing
  Image matting
  Computational geometry
  Hierarchical representations
  Speed-up techniques for real-time rendering
  Shadows: hard shadows, soft shadows
  Point set and image registration
  
  The topics are explained with both mathematical description as well as its algorithmic counterpart. Students will learn theoretical basis of the above-described concepts, algorithms, and representations.

PA017 Software Engineering II

zk 2/0 2 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Goals: The goal of this course is to explain software engineering approached in managing work on large projects.
• Learning outcomes: At the end of the course students should be able to:
  understand and explain problems of measuring effects of information technologies.
  make reasoned decisions about the benefits of information technologies;
  make reasoned decisions about the support of administration and management in the software life-cycle, together with related social and ergonomic issues.
• Syllabus: SW development process. The main activities in the development process and different approaches.
  RUP in terms of development and management activities.
  Configuration management, software version control, refactoring and integration.
  The issue of testing and test process management, use case driven testing.
  Types of tests, testing tools, automation testing, incident management. A user interface, the design, and tuning.
  Software metrics, refactoring.
  Software maintenance, software reusability.
  Debugging and deployment.
  SW quality and evaluation, ISO 9000, ISO 14598.

PA018 Advanced Topics in Information Technology Security

zk 1/1 4 kr., podzim

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - Mgr. Kamil Malinka, Ph.D. - doc. RNDr. Tomáš Pitner, Ph.D. - RNDr. Adam Kučera, Ph.D. - RNDr. Daniel Tovarňák, Ph.D.
• Prerequisities: PV017 || PV079 || PV157 || IV054
  Knowledge of English (intermediate level). Students shall also pass at least one of the following courses (PV017, PV079, PV157, IV054) before registering this course.
• Goals: To teach the students to:
  understand advanced concepts in designing, developing, managing and analyzing security systems;
  review inter-dependencies between system components and point out major vulnerabilities;
  design security mechanisms;
  reflect requirements and demands that have to be addressed when solving problems and security issues in common computer systems;
  create both written project report and (oral) presentation of the project;
  argue for their solution or analysis in the ways implied above.
• Learning outcomes: Graguate of this course shall be able to:
  understand advanced concepts in designing, developing, managing and analyzing security systems;
  review inter-dependencies between system components and point out major vulnerabilities;
  design security mechanisms;
  reflect requirements and demands that have to be addressed when solving problems and security issues in common computer systems;
  create both written project report and (oral) presentation of the project;
  argue for their solution or analysis in the ways implied above.
• Syllabus: This advanced-level course reviews selected topics in IT security in a greater depth. Students are expected to work on several assignments and a term project.
  This course is given in English. Assignments and the term project are to be handed in also in English, yet final exam answers are accepted in both Czech and English. Guest lectures of industry experts will complement the core topics lectured. Topics include issues related to the following areas:
  Applications of cryptographic mechanisms, namely of public key techniques. Key management and protocols.
  Security policies. Risk assessment and analysis. Role of standards and evaluation (criteria).
  Authentication, namely issues of biometric authentication.
  Security in communications and networks.
  Secure hardware, smartcards.
  Trust, electronic and/vs. real relations.
  Malware.
  Security of critical infrastructures.

PA026 Artificial Intelligence Project

k 0/2 2 kr., jaro

• doc. RNDr. Aleš Horák, Ph.D.
• Prerequisities: PB016
  
• Goals: The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Artificial Intelligence I.
• Learning outcomes: Students will be able to:
  - design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
  - present the selected step-by-step approach;
  - justify the chosen implementation process;
  - design an evaluation process of the created application and process its results.
• Syllabus: Study of a chosen area of artificial intelligence
  Project implementation.

PA036 Database System Project

z 0/2 2 kr., jaro

• doc. RNDr. Vlastislav Dohnal, Ph.D.
• Prerequisities: Knowledge of database systems, data modeling and software engineering is expected and positive attitude to programming
• Goals: The aim of the course is to analyze and create the assigned problem from the area of data processing, implement a solution to the problem and present results, typically performance results. The implementation assumes the use of a current database system, not excluding database installation in portable devices.
• Learning outcomes: Upon completion of the course the student will be able to: - use a database storage system; - study and use advanced data processing techniques; - design and implement application performance tests; - document the test results and present them.
• Syllabus: Presenting project topics, creating a detailed assignment.
  Planning and managing project implementation using the GANTT chart.
  Project solution consultation.
  Presentation of a project solution proposal.
  Implementing the solution and consulting it.
  Executing performance tests.
  Presentation of the project implementation, results achieved and evaluation of the work time schedule.

PA037 Compiler Project

z 0/2 2 kr., jaro

• prof. RNDr. Antonín Kučera, Ph.D.
• Prerequisities: PA008 Compiler Construction
• Goals: The aim of the seminar is to provide students with a deeper knowledge about the structure of programming languages and the funcionality of the corresponding compilers. To pass this seminar, students have to design a simple programming language and implement its compiler. It is possible to work in groups of 2-4 members; the complexity of the project should be proportional to the number of group members.
  Main objectives of the course can be summarized as follows: to understand basic design principles of programming languages and their compilers; to design a simple programming language and implement its compiler.
• Learning outcomes: Own experience with implementation of a compiler.
• Syllabus: The logical structure of a compiler. Formalisms used to specify the individual modules.
  The scanner. Regular expressions. Tokens and their precedence.
  The parser. Top-down and bottom-up analysis.
  The constrainer. Attribute grammars. Attribute flow. Attribute evaluation.
  The code generator, optimisations.
  A complete specification of a simple one-pass optimising compiler.
  Symbol tables as attributes. Declarations, type checking, scope analysis.
  Functions. Stack frames. Passing of parameters. Conventions of C and Pascal.
  Input and Output. Unix and the C language.
  I386 assembler, conventions of the C language.

PA039 Supercomputer Architecture and Intensive Computations

zk 2/0 2 kr., jaro

• prof. RNDr. Luděk Matyska, CSc.
• Prerequisities: ! IA039
  At least elementary knowledge of programming languages FORTRAN, C and eventually C++ is expected.
• Goals: The main goal of this lecture is to provide information about architectures of high-performance computing systems and basic programming methods for vector and parallel computers. The first part focuses on the hardware, during the second part general optimization methods and programming methodology for parallel computers is discussed. The last part of the lecture is aimed at the programming of distributed systems.
• Learning outcomes: The graduate will be able to understand and explain properties of modern processors.
  The graduate will be also able to analyze the program code and propose optimizations for a particular processor.
  The graduate will be able to design and implement a simple parallel program to solve a particular problem.
  The graduate will be able to design and realize benchmarks of computer systems or applications.
• Syllabus: High-performance vector and superscalar processors.
  Uniprocessor computers, computers with a small number of processors, massively parallel computers; distributed systems.
  Performance measurements, LINPACK test, TOP 500 list.
  High-performance uniprocessor systems, programming languages, the methodology of efficient program writing, basis optimization methods for vector and superscalar computers.
  Distributed systems, data and task decomposition, coarse grain parallelism, programming systems (PVM, LINDA, ...). Multiprocessor systems with shared memory, programming languages, decomposition of algorithms, basic optimization methods for a small number of processors.
  Massively parallel systems, parallel algorithms, fine grain parallelism.
  Shared, distributed, and distributed shared memory; other alternatives. Sdílená, distribuovaná a distribuovaná sdílená paměť.
  Scalability of computers and tasks.

PA052 Introduction to Systems Biology

zk 2/0 2 kr., jaro

• prof. RNDr. Luboš Brim, CSc. - doc. RNDr. David Šafránek, Ph.D.
• Goals: Graguate of this course shall be able to: understand the basic concepts of systems biology; understand the role of computer-science in systems biology; employ abstract computer-scientific thinking in the field of biological systems modeling.
• Learning outcomes: After the course the student will be able:
  - to analyse and discuss pros and cons of computational methods in systems biology;
  - to interpret the paradigm of systems biology;
  - to identify basic tasks employed in systems biology;
  - to judge ideas and opinions in front of students and the teacher.
• Syllabus: History and scope of systems biology.
  Elementary biological notions.
  Elementary notions of systemic paradigm - biological process studied in terms of a complex system.
  Model organisms.
  Sources of biological data - Databases of biological knowledge.
  Research scenario in systems biology, role of computer science.
  Models in systems biology, model databases.
  Examples of systems biology application.
  Design and reconstruction of biological networks - Synthetic Biology.
  Information in biology and about biology.

PA053 Distributed Systems and Middleware

zk 2/0 2 kr., jaro

• RNDr. Michal Batko, Ph.D.
• Goals: The goal of the course is to introduce possible solutions to problems related to the design of a robust distributed application.
• Learning outcomes: At the end of the course students should be able to:
  understand and explain the abstractions provided by operating systems and middleware layers in a distributed environment
  organize an analysis of the communication, replication, sharing issues,
  work with information on the abstractions provided by the distributed operating system kernels,
  work with information on the abstractions provided by the middleware layers,
  assess specific system studies,
  use modern technologies to create distributed applications.
• Syllabus: Distributed system concepts, benefits, problems, typical architectural patterns (single system image, client-server, service oriented).
  Technological solutions related to distributed systems (communication, replication, sharing, migration).
  Operating systems and middleware for distributed systems, provided abstractions, and specific system studies (CORBA, RMI, JMS, EJB, WS, , and others).

PA054 Formal Methods in Systems Biology

zk 2/0 2 kr., jaro

• doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: The course requires elementary knowledge of formal techniques achieved at bachelor level. This is an interdisciplinary course. The course is recommended especially for students of Bioinformatics. The course is also suitable for students of all other applied and theoretical study branches, namely Parallel and Distributed Systems and Theoretical Computer Science.
• Goals: At the end of this course students should be able to: understand the actual trends and open problems in the domain of formal methods for complex systems modeling; apply formal methods in the modern biological research in systems biology; employ relevant software tools to solve particular problems in modeling and simulation of biological systems.
• Learning outcomes: At the end of this course students should be able to:
  - define the actual problems solved in the domain of formal methods for complex systems modelling and analysis;
  - apply formal methods in systems biology;
  - use relevant software tools to solve particular problems in modeling and simulation of biological systems.
• Syllabus: Problem definition: Modeling and analysis in systems biology. Motivation for application of formal methods.
  Overview of formal methods employed for analysis of biological hypotheses. Model specification. Model size and state explosion problem.
  Modeling and simulation: Deterministic vs. non-deterministic models. Continuous vs. discrete models. Models with parameter uncertainty. Approximation and abstraction. Simulation and analysis.
  Qualitative models: Boolean networks, Petri nets.
  Quantitative models: Timed Boolean networks, Markov chains, Stochastic Petri nets, relations to continuous and hybrid models.
  Formal specification of models: Kappa-calculus, Stochastic Petri nets, Stochastic Pi-Calculus and related formalisms.
  Model checking: Application in the process of model validation. Properties of in silico models vs. in vivo/in vitro experiments. Model checking tools for biological models.
  Models with parameter uncertainty: Parameter estimation. Robustness analysis.

PA055 Visualizing Complex Data

zk 1/1 2 kr., podzim

• Ing. Matej Lexa, Ph.D.
• Prerequisities: Elementary programming skills and interest in R and Processing (scripting and programming languages)
• Goals: Students will get aquainted with complex data in bioinformatics and selected other disciplines and their visualization, using examples in R and PROCESSING languages or scientific literature.
• Learning outcomes: At the end of the course students will be able to:
  explain the basic principles and goals of visualization
  prepare data for visualization
  evaluate existing visualizations
  create their own static or interactive visualization
• Syllabus: 1. Introduction to data visualization
  2. The R computing environment and its visualization tools
  3. The Processing computing environment and its visualization tools
  4. Visualization and data types in bioinformatics and system biology
  4. Data preprocessing (dimensionality estimates and reduction, PCA, clustering, similarity metrics, multidimensional scaling)
  6. Review of isualization techniques (plots, histograms, trees and other graphs, maps, hybrid visualization)
  7. Examples of visualization in bioinformatics, systems biology and other disciplines

PA093 Computational Geometry Project

z 0/1 2 kr., podzim

• doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: It is recommended to concurrently attend or finish the M7130 course before attending this course. Moreover, the student should have the knowledge of C++ or Java programming language.
• Goals: The project is focused on solving the tasks from computational geometry area. The aim is programming and visualization of classical 2D and 3D algorithms. Students gain practical experience in implementation and integration of complex algorithms from the field of computer graphics.
• Learning outcomes: After passing this course, the student will be able to: - compare computational geometry algorithms with respect to their complexity, - choose the most appropriate computational geometry algorithms for given problems, according to their complexity and input requirements, - implement computational geometry algorithms described by a pseudocode.
• Syllabus: The purpose of this seminar is to discuss, extend and elaborate the subject area presented in M7130 , especially with respect to its practical applications. Some selected geometric algorithms will be implemented during the course. The aim of the first task is to demonstrate the problems regarding programming of computational geometry algorithms. Then an implementation of an essential and substantially more complicated advanced algorithm follows. Students gain practical experience with the implementation of advanced computational geometry applications.

PA096 Seminar of Dialog Laboratory

k 0/2 2 kr., podzim

• doc. RNDr. Ivan Kopeček, CSc. - RNDr. Jaromír Plhák, Ph.D.
• Prerequisities: souhlas
  
• Goals: The aim of the seminar is to create a common platform for discussing issues related to ongoing research projects within the laboratory . The purpose is to present current projects' status to the other lab members and stir up a discussion that leads to new solutions and approaches. The projects are solved within small, usually disjoint, teams but led by lab members.
• Learning outcomes: After completing this course, student will be able to:
  - to present the state of the art of the research projects solved within the laboratory;
  - present a research summary on the topics related to the areas of expertise of the laboratory.
• Syllabus: The content of the seminar is formed by presentations of current status of ongoing research projects of the laboratory . An inherent part of the seminar constitutes presentations of new research trends. The backbone of the seminar is formed by presentations by PhD students.

PA096 Seminar of Dialog Laboratory

k 0/2 2 kr., jaro

• doc. RNDr. Ivan Kopeček, CSc. - RNDr. Jaromír Plhák, Ph.D.
• Prerequisities: souhlas
  
• Goals: The aim of the seminar is to create a common platform for discussing issues related to ongoing research projects within the laboratory. The purpose is to present current projects' status to the other lab members and stir up a discussion that leads to new solutions and approaches. The projects are solved within small, usually disjoint, teams but led by lab members.
• Learning outcomes: After completing this course, student will be able to:
  - to present the state of the art of the research projects solved within the laboratory;
  - present a research summary on the topics related to the areas of expertise of the laboratory.
• Syllabus: The content of the seminar is formed by presentations of current status of ongoing research projects of the laboratory An inherent part of the seminar constitutes presentations of new research trends. The backbone of the seminar is formed by presentations by PhD students.

PA103 Object-oriented Methods for Design of Information Systems

zk 2/0 2 kr., podzim

• RNDr. Radek Ošlejšek, Ph.D.
• Prerequisities: Knowledge of object-oriented programming principles, core knowledge of software engineering, knowledge of UML models.
• Goals: Understand object-oriented fundamentals that are used across all the levels of OO decomposition;
  Ability to select and apply suitable formal models (UML, OCL) in various levels of decomposition;
  Ability to select and apply suitable patterns during a system decomposition;
  Understand the term "software quality" in the context of code, object-oriented models, and software architectures; Application of tuning tactics for quality improvement;
• Learning outcomes: At the end of the course, a student should be able to:
  - explain fundamentals of object-oriented design and development;
  - express semantic constraints on object-oriented models by means of Object Constraint Language;
  - identify "bad smells" in code and apply suitable refactoring tactics;
  - explain properties of analysis, design, and architectural patterns;
  - apply analysis, design, and architectural patterns to system decomposition;
  - describe properties and processes related to the development of component systems;
  - explain qualitative aspects of software and describe their tuning tactics;
• Syllabus: Object-oriented paradigm, object properties, principles of abstraction and decomposition. Principles of OO analysis and design.
  Models of classes, packages and components. Interface as contract. IDL, SWDL.
  Refinement of UML semantics by means of stereotypes and OCL.
  Software re-use, software patterns at various stages of software life cycle (analysis, design, architecture, coding).
  Design patterns in detail.
  Analysis patterns, Java patterns, anti-patterns.
  Code refactoring („refactoring to patterns“).
  Software architectures, architectural patterns.
  Component systems. Qualitative attributes and their evaluation.
  Object-oriented methods for software development, application of UML models in RUP.
  Special methods and architectures: MDD, FDD, SOA, ...
  Model-Driven Architecture (MDA), employing OCL in MDA.

PA107 Corpus Tools Project

z 0/2 2 kr., jaro

• doc. Mgr. Pavel Rychlý, Ph.D.
• Goals: The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of corpus linguistics and practical checking of this knowledge by working on the project. The popularisation of corpus linguistics and other areas of language engineering is one of the main goals of Natural Language Processing Laboratory at the Faculty of Informatics.
  Fundamental information about the Natural Language Processing Laboratory and corpus linguistics in general can be found on http://www.fi.muni.cz/nlp/.
• Learning outcomes: Student will be able to: create a text corpus from different sources; use automatic tools for corpus annotation; evaluate accuracy of automatic tools; present evaluation results.
• Syllabus: The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of corpus linguistics and practical checking of this knowledge by working on the project. The popularisation of corpus linguistics and other areas of language engineering is one of the main goals of Natural Language Processing Laboratory at the Faculty of Informatics.
  Fundamental information about the Natural Language Processing Laboratory and corpus linguistics in general can be found on http://www.fi.muni.cz/nlp/.

PA116 Domain Understanding and Modeling

zk 2/2 3 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D. - RNDr. Josef Spurný
• Prerequisities: The knowledge of introductory database and data modeling courses are required.
• Goals: Systematic approach to understanding of the domain in which a service system will operate based on conceptual modeling. Semantics modeling of services underlying structures.
• Learning outcomes: At the end of this course students should be able to:
  understand the step-by-step service system modeling and evaluation;
  use analytical patterns in data modeling and perform component consolidation;
  manage knowledge and information;
  understand conceptual systems, higher-order objects, and their role in service systems design;
  work with abstract data types and use OOP and connection oriented paradigm;
  design conceptual and behavioral models of a given domain.
• Syllabus: Systematic approach to understanding of the domain in which a service system will operate based on conceptual modeling. Semantics modeling of services underlying structures.
  Service systems and how to understand its domain
  Transparent intensional logic and natural language analysis
  Information, knowledge and their modeling
  Concepts and objects, high order objects
  HIT-attributes, definability, decomposability. Semantics and information capability
  Modeling, modeling tools, modeling capability, universality principle, self-reference, MENTION-USE principle
  OO approach, data abstractions, OO software construction and OO analysis. Issues in OO analysis
  Connection oriented paradigm (COP). Service system domain understanding and modeling using COP approach and contexts.

PA128 Similarity Searching in Multimedia Data

zk 2/0 2 kr., jaro

• prof. Ing. Pavel Zezula, CSc.
• Goals: The objective of the course is to introduce the idea of similarity search on unstructured data and define basic similarity queries and data partitioning principles. Based on these fundamentals, the current state of the art of centralized, approximate, and distributed index structures is presented.
• Learning outcomes: Upon successful completion of the course student will be able:
  to understand principles of similarity searching;
  to apply similarity searching paradigm to multimedia data;
  to explain principles of index structures for multimedia data;
  to implement an index structure introduced in the course.
• Syllabus: Part I Metric Searching in a Nutshell:
  Foundations of Metric Space Searching
  Survey of Existing Approaches
  
  Part II Metric Searching in Large Collections of Data:
  Centralized Index Structures
  Approximate Similarity Search
  Parallel and Distributed Indexes.

PA150 Advanced Operating Sytems Concepts

zk 2/0 2 kr., podzim

• doc. Ing. Jan Staudek, CSc.
• Prerequisities: Computer systems architectures, operating systems - user view
• Goals: At the end of the course students will be able understand application-oriented systems for faut-tolerant transaction processing based on multitasking operating systems operating in a distributed environment.
• Learning outcomes: Students completing the course will be able to:
  - Designing aplication systems oriented on fault tolerant transactional processing based multitasking operating systems
  - Designing aplication systems oriented on distributed systems
• Syllabus: Selected topics characterizing key operational functionality and their related systems whose understanding easier and more efficient design and implementation of nontrivial application (intentionally distributed) systems
  Distributed systems, roles and principles of operating systems
  Time and state in a distributed environment
  Transaction processing incl. management of concurrent transactions renewal after an fault as an example of a complex application over services running operating systems
  Deadlock concurrent activities (processes, threads, transaction,...)
  Distributed solutions typical synchronization tasks: mutual exclusion, consensus, multicasting,...
  Concurrency control of transaction and deadlock solutions in a distributed environment

PA151 Advanced Computer Networks

zk 2/0 2 kr., jaro

• doc. Ing. Jan Staudek, CSc.
• Prerequisities: Networking principles, basic network architectures, data communication basics
• Goals: At the end of the course students should be able
  apply medium access technology for wireless links
  describe and explain WPAN, Wireless Personal Area Networks, Bluetooth, Zigbee, ...
  describe and explain WLAN, Wireless Local Area Networks, Wi-Fi, 802.11
  describe and explain Cellular transmission principles ,GSM, GPRS, EDGE, UMTS, LTE
  describe and explain Satellite communications
  describe and explain WMAN, Metropolitan Networks (WiMAX/802.16)
  describe and explain Cordless systems and wireless local loop, FWA
• Learning outcomes: Students will be able to understand
  medium access technology for wireless links
  WPAN, Wireless Personal Area Networks, Bluetooth, Zigbee, ...
  LAN, Wireless Local Area Networks, Wi-Fi, 802.11
  Cellular transmission principles , GSM, GPRS, EDGE, UMTS, LTE
  Satellite communications
  WMAN, Metropolitan Networks (WiMAX/802.16)
  Cordless systems and wireless local loop, FWA
• Syllabus: Technical Background of Networking: transmission fundamantals, communication networks, protocols and protocol suites
  Wireless Communication technology: antenas and propagation, signal encoding, spread spectrum, error control
  Wireless Medium Access
  WPAN, Wireless Personal Area Networks, Bluetooth, Zigbee, ...
  WLAN, Wireless Local Area Networks, Wi-Fi, 802.11
  Cellular transmission principles ,GSM, GPRS, EDGE, UMTS, LTE
  Satellite communications
  WMAN, Metropolitan Networks (WiMAX/802.16)
  Cordless systems and wireless local loop, FWA

PA152 Efficient Use of Database Systems

zk 2/0 3 kr., jaro

• doc. RNDr. Vlastislav Dohnal, Ph.D.
• Prerequisities: Knowledge of problems in the extent of PB154 Database Systems (or PB168) and PV062 File Organization courses.
• Goals: The aim of the course is to become familiar with the capabilities of database systems and their efficient use.
• Learning outcomes: Student will be able to:
  - understand the principles of relational database systems;
  - analyze performance of query processing;
  - optimize processed queries both by rewriting them and by creating indexes and applying other techniques;
  - Explain principles of logging and recovery from failure;
  - Design basic replication strategies to achieve high availability;
  - Design a disk storage for the database system.
• Syllabus: Introduction
  Data storage: efficient use of secondary storage, records, blocks. Searching: index structures, sequential files, trees, hashing, multidimensional indexes.
  Query execution: evaluation plan, algebraic laws, cost estimation, algorithms for operators, sorting and joining relations, query execution and pipelining.
  Query optimization: contribution of indexes, referential integrity, materialized views, table partitioning, disk storage.
  Database optimization: relational schema tuning, index optimization, database monitoring tools.
  Transaction management: properties and their implementation, concurrency control, scheduling, data and index locking, logging and recovery from failures.
  Database security: access rights, data security.
  Spatial databases: indexes, operators.
  Analytical tools.

PA153 Natural Language Processing

zk 2/0 2 kr., podzim

• prof. PhDr. Karel Pala, CSc. - Mgr. Vít Nováček, PhD
• Goals: The course offers a deeper knowledge about the natural language processing and computational linguistics.
• Learning outcomes: The students will learn about the particular levels of linguistic analysis - morphology, syntax, semantics and pragmatics.
  They will be able to use language data - corpora, types of corpora, corpus tools, perform tagging corpus texts, disambiguation with rule based and statistical systems.
  They will be acquainted with representation of the morphological stuctures, notation and algorithms for morphological analysis.
  The students will be able to work with the representations of syntactic structures - formal grammars and their types. They will learn about context-free, functional and definite-clause grammars and related parsing algorithms.
  The data structures such as valency frames and their types will be explained as well.
  They will learn about lexical semantics - meanings of words and collocations, machine readable dictionaries, lexical databases (WordNet, EuroWordNet, thesauri).
  Semantic analysis of sentence, principles of logical semantic and Normal Translation Algorithm will be presented.
  Pragmatics and discourse analysis and its segmentation, anaphora and (co-)reference will be explained.
  The students obtain basic knowledge about dialogue systems, inference systems and knowledge representation for NLP systems.
  They will be able to understand the principles of the communication agents and main evaluation techniques.
• Syllabus: Natural language processing and computational linguistics.
  Natural language and understanding.
  Levels of linguistic analysis - morphology, syntax, semantics.
  Language data - corpora. Types of corpora. Corpus tools. Tagging corpus texts. Disambiguation, rule based and statistical systems.
  Representation of the morphological stuctures, notation, morphological algorithms.
  Representation of syntactic structures - formal grammars and their types. Context-free and definite-clause grammars. Parsing algorithms. Valency frames and their types.
  Semantic representation. Lexical meanings (words and collocations), machine readable dictionaries, lexical databases (WordNet, EuroWordNet, thesauri).
  Semantic analysis of sentence meaning, Normal Translation Algorithm.
  Pragmatics.
  Discourse analysis and its segmentation. Anaphora and (co-)reference.
  Inference and knowledge representation for NL systems.
  Dialogue systems.
  Communication agents.
  Evaluation techniques

PA154 Language Modeling

zk 2/0 2 kr., jaro

• doc. Mgr. Pavel Rychlý, Ph.D.
• Goals: This course aims at providing the students with state-of-the-art in (mainly statistical) methods, algorithms and tools used for processing of large text corpora when they are created or subject to subsequent information retrieval.
  These tools are practically used in many areas of natural language processing (semiautomatic building of text corpora, morphological analysis and desambiguation, syntactic analysis, effective indexation and search in text corpora, statistical machine translation, semantic analysis etc.).
• Learning outcomes: At the end of the course students will be able to: use tools containing language models; understand the related theories and algorithms; include probabilistic models in the design of text processing applications; implement selected techniques in own applications.
• Syllabus: Elements of Probability and Information Theory
  Language Modeling in General and the Noisy Channel Model
  Smoothing and the Expectation-Maximization algorithm
  Markov models, Hidden Markov Models (HMMs)
  Viterbi Algorithm
  Tagging methods, HMM Tagging, Statistical Transformation Rule-Based Tagging
  Statistical Alignment and Machine Translation
  Text Categorization and Clustering
  Graphical Models
  Parallelization, MapReduce

PA156 Dialogue Systems

zk 2/0 2 kr., jaro

• Mgr. Luděk Bártek, Ph.D.
• Goals: Basic aspects of the current theory of dialogue systems, their implementations and applications are presented in the course. The basic goal is to present an overview of the state of the art in the field and to outline the future perspective.
• Learning outcomes: Student will be able to design dialogue systems using the approriate up-to-date technologies.
• Syllabus: History of the human-computer communication (Elisa, expert systems, virtual reality)
  Basic technologies of the dialogue systems (principles of the speech synthesis and recognition, multi-modal interface)
  Principles of the natural language analysis (formal models, Chomsky approach, other alternatives, statistical approach, semantic and pragmatic analysis)
  Structure and models of dialogue, basic types of dialogues (Conversational analysis, principles and characteristics of the cooperative and non-cooperative dialogue)
  Dialogue strategies (Types of dialogue strategies, relations with the game theory)
  Syntax, semantics and pragmatics of dialogue (Formal description of dialogue and dialogue strategies, methods of semantics analysis, pragmatic aspects)
  Modelling and processing emotions (Emotions meaning for dialogue strategies, detection and analysis of emotions)
  Sentence interpretation and generation (Ambiguities, context)
  Structure of dialogue systems (basic modules of dialogue systems and their function)
  Dialogue languages, W3C Voice Browser Activity Standards (VoiceXML, SRGS, SISR, SSML, etc., dialogue notation)
  User modelling (UM and relations to dialogue systems)
  Simulation a testing dialogue system (methods of simulation and testing, the method WOZ)
  Implementations a applications, future of dialogue systems

PA157 Seminar on Computer Graphics Research

k 0/2 2 kr., podzim

• doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: Theoretical and practical knowledge of computer graphics foundations.
• Goals: The participants of research seminar discuss classical and current research papers related to computer graphics. Students are expected to read relevant research papers, prepare and give presentations and to engage actively in discussion during seminar hours. They get acquainted with the contemporary computer graphics trends and improve their rhetorical skills.
• Learning outcomes: At the end of the course students
  - will be familiar with current trends in Computer Graphics research;
  - will be able to prepare a sound presentation for CG professionals;
  - will understand the broader context of traditional and new research topics in CG;
  - will improve their rhetorical and presentation skills;
  - will enhance their abilities to discuss non-trivial theoretical problems.
• Syllabus: The study of classical and current research papers related to computer graphics. At the beginning of the semester, students are offered the selection of new research papers published at the high-rank conferences on computer graphics and related areas. The papers are selected from the latest conferences SIGGRAPH, SIGGRAPH Asia, EUROGRAPHICS or similar. Students chose a research paper and then they look up related "predecessor" paper. They prepare and give 2 presentations of research articles, predecessor paper followed by the latest paper. Students present the latest research advances and discuss them in a broad context.

PA159 Net-Centric Computing I

zk 2/0 2 kr., podzim

• doc. RNDr. Eva Hladká, Ph.D.
• Prerequisities: ! PA191 && ! NOW ( PA191 )
  
• Goals: The main goal of this course is to provide a deeper insight into the area of computer networks (behind the level of basic bachelor courses) and to provide a complex survey of crucial protocols in computer networks (routing, IPv6, quality of service, etc.).
  Graduate will learn the basic principles in the area of mobile networks, he or she will obtain an idea about their specific features from the perspective of computer networks.
  Graduate will be also able to prepare and lead simple courses targeted in particular areas of computer networks and their applications.
• Learning outcomes: Graduate will be able to analyze the behavior of even complex computer networks and propose their topology as well as solutions to particular problems.
  Graduate will also know the features and benefits of the IPv6 network protocol and become able to design and implement an IPv6 network.
  Graduate will obtain a survey of mechanisms used for ensuring the quality of service in computer networks.
  Graduate will be able to discover bottlenecks in communication systems and will be able to propose their removal/elimination.
  Graduate will learn the basic principles in the area of mobile networks, he or she will obtain an idea about their specific features from the perspective of computer networks.
• Syllabus: Architecture of computer networks, ISO/OSI and TCP/IP model, IP protocol, transport protocols (TCP, UDP), basic services of computer networks -- short recapitulation.
  Advanced features of IPv6 protocol: mobility and security, ICMPv6, IPv6 support in applications.
  Advanced routing mechanisms: distance vector, link state and path vector routing. Router architecture. Traffic Engineering. MPLS, MPLS labels' assignment and distribution, MPLS routing.
  Advanced TCP protocol features. Protocols for high bandwidth networks with high latency.
  Peer-to-peer networks. Basic architectures, routing in structured and unstructured P2P systems and hybrid P2P networks.
  Ad-hoc/sensor networks: history, types, data transmission principles, communication principles, routing, mechanisms for ensuring reliable communication, protocols, actual trends.
  Computer networks and multimedia: multimedia applications, application demands, actual trends.

PA160 Net-Centric Computing II

zk 2/0 2 kr., jaro

• prof. RNDr. Luděk Matyska, CSc. - RNDr. Martin Kuba, Ph.D. - doc. RNDr. Vojtěch Řehák, Ph.D.
• Goals: The main goal of this lecture is to give insight to principles of new generation of Internet protocols at one side and to show how originally network services are becoming part of higher, application-oriented layers. Networks are presented as a basic construction brick of (large) distributed systems. These form the focus of the next part of the lecture, where their function, design, and implementation are discussed. A brief introduction into mobile computing closes the lecture.
• Learning outcomes: The graduate will understand network protocols and will have an overview of their usability for a particular application.
  The graduate will have basic orientation in the area of web and grid services, will be able to implement simple services.
  The graduate will understand basics of distributed computing and the underlying network protocols and will be able to design a simple distributed system in a specified environment.
  The graduate will understand work with time in the networked environment.
• Syllabus: Computer networks security: cryptography, secure computer networks machinery.Examples of typical protocols. Basic computer network attacks and basic method of defense.
  Computer network management, components, and protocol of network management (SNMP).
  Distributed applications: characteristic, properties and architecture. RPC, directory services. Distributed objects principals, COM, RMI, CORBA. Web and grid services.
  Distributed systems, splitting, and allocation of distributed tasks, load balancing (static, dynamic). Fault tolerance, recovery. Languages and tools for distributed systems.
  Basics of network protocols design, verification.
  Experiments in computer networks, simulators, and emulators.

PA163 Constraint programming

zk 2/1 3 kr., podzim

• doc. Mgr. Hana Rudová, Ph.D.
• Goals: Course provides information about constraint programming, about problem modeling using constraints generally as well as practically in programming language, about general propagating algorithms and about main search algorithms for constraint satisfaction problems.
• Learning outcomes: The graduate will understand how to apply a declarative approach for problem solving with the help of constraint programming.
  The graduate will understand which algorithms are used for the implementation of the constraint programming approach to be able to propose a proper declarative model and proper search procedures. To achieve that graduates will learn various constraint propagation algorithms and search methods.
  The graduate will be able to implement a solution to the problem using constraint programming in the Optimization Programming Language of IBM CPLEX CP Optimizer.
• Syllabus: Constraint satisfaction problem. Introduction to problem modeling.
  Algorithms and consistency: arc, path. Methods for non-binary constraints: k-consistency, general arc, and bounds consistency, global constraints. Directional versions, the width of the constraint graph, and polynomial problems.
  Tree search: backtracking, look ahead, look back, incomplete algorithms. Local search.
  Optimization and over-constrained problems: frameworks and algorithms.
  Problem modeling and real-life applications. Programming with programming language OPL in IBM ILOG CP Optimizer.

PA164 Machine learning and natural language processing

zk 2/1 3 kr., podzim

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Goals: Students will obtain knowledge about methods and tools for text mining and natural language learning. At the end of the course students should be able to create systems for text analysis by machine learning methods. Students are able to understand, explain and exploit contents of scientific papers from this area.
• Learning outcomes: A student will be able
  - to pre-process text data for text mining;
  - to build a system for analysis of text by means of machine learning;
  - to understand research papers from this area;
  - to write a technical report.
• Syllabus: Natural language processing(NLP). Corpora. Tools for NLP.
  Inroduction to machine learning
  Disambiguation. Morphological disambiguaiton and word-sense disambiguation
  Shallow parsing and machine learning
  Entity recognition and collocations
  Document categorization
  Information extraction from text
  Text mining
  Web mining
  Applications: text with spatio-temporal information, biomedical and biological texts.

PA165 Enterprise Applications in Java

zk 2/2 3 kr., jaro

• Bruno Rossi, PhD - doc. RNDr. Tomáš Pitner, Ph.D. - Ing. Petr Adámek - RNDr. Martin Kuba, Ph.D. - Jan Pačes - Mgr. Vítězslav Papiež
• Prerequisities: Knowledge of Java at the level of PB162 and PV168 courses. Basic knowledge of markup languages (XML and/or HTML) and databases are also expected.
• Goals: Students will understand selected chapters from advanced Java-based system design and implementation; they will be aware of methodological issues of high-quality program system design and implementation and related topics; they will be able to work with the most important APIs from Java SE, Spring framework, Java EE and Javascript frameworks for UI. Students will get acquainted with team work within large enterprise software development and with system design by applying enterprise patterns.
• Learning outcomes: Student will be able to:
  - use advanced development tools for enterprise development in real life;
  - apply design and implementation patterns for enterprise applications in own systems;
  - write applications using persistence / ORM;
  - create Internet-based applications with servlets, JSP, taglibs;
  - handle the basic application security (authentication, authorization), be able to identify the basic types of attacks against the main IS;
  - create a basic web user interface based on HTML, CSS, javascriptive frames;
  - apply the Spring framework (AOP, dependency injection, security, transactions, Spring Boot);
  - clarify the meaning and the purpose of Web Services (REST, WS- * Standards), use frameworks for their creation and be able to implement them in simple systems;
  - know what Messaging Systems based on JMS are, and be able to use them in practical systems.
• Syllabus: Intro to large (enterprise) Java-based application and systems
  Development tools (Netbeans, Maven, Git)
  Enterprise patterns (DTO, DAO)
  Persistence/ORM (JPA/Hibernate)
  Internet applications (servlets, JSP, taglibs, Java web containers)
  Web application layers, security (authentication, authorization, main attacks), Spring MVC, client-side javascript frameworks (AngularJS), HTML, CSS, DOM
  Spring framework (AOP, dependency injection, security, transactions, Spring Boot)
  Web services (REST, WS-* standards), Spring-WS, JAX-RS
  Messaging Systems (JMS)

PA166 Advanced Methods of Digital Image Processing

zk 2/2 3 kr., jaro

• doc. RNDr. Pavel Matula, Ph.D.
• Prerequisities: PV131
  Knowledge at the level of the lecture PV131 Digital Image Processing is assumed.
• Goals: At the end of the course students should be able to: understand the basics of state-of-the-art mathematically well-founded methods of digital image processing; numerically solve basic partial differential equations and variational problems of digital image processing.
• Learning outcomes: At the end of the course students should be able to: understand the basics of state-of-the-art mathematically well-founded methods of digital image processing; numerically solve basic partial differential equations and variational problems of digital image processing.
• Syllabus: Image as a function, computation of differential operators
  Linear diffusion and its relation to Gaussian blurring
  Nonlinear isotropic diffusion
  Nonlinear anisotropic diffusion
  Variational filtering
  Mathematical morphology as a solution of PDE (dilation and erosion), shock filtering
  Parametric active contours (snakes)
  Fast marching algorithm, basics of level set methods
  Level-set methods (basic numerical schemes)
  Segmentation (geodesic active contours, Mumford-Shah and Chan-Vese funkcionals)
  Optical flow
  Minimization based on graph-cuts

PA167 Scheduling

zk 2/0 2 kr., jaro

• doc. Mgr. Hana Rudová, Ph.D.
• Goals: The course provides information about various types of scheduling problems from theoretical and practical perspective. It demonstrates general solution approaches for scheduling problems and the most important approaches for various classes of scheduling problems from practice.
• Learning outcomes: Graduate will be able to identify and describe various scheduling problems appearing in practice.
  Graduate will be aware of general methods applicable to solve scheduling problems from in manufacturing and services.
  Graduate will be aware of algorithms and solution methods for scheduling problems such as project planning, scheduling of flexible assembly systems, or educational timetabling.
  Graduate will be able to solve scheduling problems with the help of studied algorithms and approaches.
• Syllabus: Examples, scheduling problem, Graham classification.
  General-purpose scheduling procedures: dispatching rules, mathematical programming, local search, constraint programming.
  Project planning and scheduling: project representation, critical path, time/cost trade-offs, workforce constraints.
  Machine scheduling: dispatching rules, branch&bound, mathematical programming, shifting bottleneck.
  Scheduling of flexible assembly systems: paced and unpaced systems.
  Reservations: interval scheduling, reservation with slack.
  Timetabling: workforce constraints, tooling constraints, relation to interval scheduling. Educational timetabling, university course timetabling.
  Workforce scheduling.

PA168 Postgraduate seminar on IT security and cryptography

k 0/2 3 kr., podzim

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - doc. RNDr. Petr Švenda, Ph.D. - doc. Ing. Jan Staudek, CSc.
• Prerequisities: souhlas
  Intermediate knowledge of IT security principles, cryptography principles. Explicit approval of the seminar supervisor must be requested in order to register this course. It is strongly suggested that Master students register this course in the last semester of their study.
• Goals: To teach the students to:
  analyze security problems and solutions with a critical mind;
  review and interpret a security solution or analysis presented in an advanced technical paper from a world-class conference;
  evaluate IT system security and relevant functional and ethical requirements and demands;
  reflect the above in their proposal for security of IT systems;
  create slides and present their own research project;
  prepare and present their view of most important developments in the area of security and cryptography during the past 1-2 weeks.
• Learning outcomes: Graduates of this course shall be able to:
  analyze security problems and solutions with a critical mind;
  review and interpret a security solution or analysis presented in an advanced technical paper from a world-class conference;
  evaluate IT system security and relevant functional and ethical requirements and demands;
  reflect the above in their proposal for security of IT systems;
  create slides and present their own research project;
  prepare and present their view of most important developments in the area of security and cryptography during the past 1-2 weeks.
• Syllabus: The seminar participants will discuss a broad range of topics in IT security and cryptography in a greater depth. PhD and Master students undertaking research in these and closely related areas are expected to report on their work, on a recent top-level conference paper and on recent developments in the field. Participants from other institutions will also take part in this seminar.

PA168 Postgraduate seminar on IT security and cryptography

k 0/2 3 kr., jaro

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
• Prerequisities: souhlas
  Intermediate knowledge of IT security principles, cryptography principles. Explicit approval of the seminar supervisor must be requested in order to register this course. It is strongly suggested that Master students register this course in the last semester of their study.
• Goals: To teach the students to:
  analyze security problems and solutions with a critical mind;
  review and interpret a security solution or analysis presented in an advanced technical paper from a world-class conference;
  evaluate IT system security and relevant functional and ethical requirements and demands;
  reflect the above in their proposal for security of IT systems;
  create slides and present their own research project;
  prepare and present their view of most important developments in the area of security and cryptography during the past 1-2 weeks.
• Learning outcomes: Graduates of this course shall be able to:
  analyze security problems and solutions with a critical mind;
  review and interpret a security solution or analysis presented in an advanced technical paper from a world-class conference;
  evaluate IT system security and relevant functional and ethical requirements and demands;
  reflect the above in their proposal for security of IT systems;
  create slides and present their own research project;
  prepare and present their view of most important developments in the area of security and cryptography during the past 1-2 weeks.
• Syllabus: The seminar participants will discuss a broad range of topics in IT security and cryptography in a greater depth. PhD and Master students undertaking research in these and closely related areas are expected to report on their work, on a recent top-level conference paper and on recent developments in the field. Participants from other institutions will also take part in this seminar.

PA171 Digital Image Filtering

zk 2/2 3 kr., podzim

• doc. RNDr. David Svoboda, Ph.D.
• Prerequisities: PV131
  Knowledge of written English and calculus is required.
• Goals: The aim of this lecture is to introduce all the basic image transforms used in digital image processing. It covers the operations of changing the image content or transforming the original data into a different representation. At the end of this course, students should be able to:
  - understand the basic principles of the image transforms;
  - know the selected transforms;
  - implement and apply the selected transforms;
  - understand standard image compression algorithms;
  - correctly resample images;
  - use suitable image restoration algorithms.
• Learning outcomes: After completing the course, the student should be able to:
  - analyze the image data in a frequency domain;
  - discuss the problems in the field of frequency analysis;
  - propose her/his own efficient and optimized compression methods;
  - demonstrate the general principles of compression algorithms;
  - use wavelet and Fourier transform appropriately;
  - solve the tasks focused on image restoration;
  - appropriately use the resampling algorithms and understand their results
• Syllabus: Discrete transforms (Fourier transform, FFT, Hadamard, DCT, Wavelets)
  Image compression, Lossy/Lossless compression, JPEG, JPEG2000, MPEG
  Sampling, Resampling, Signal reconstruction, Texture filtering
  Z-transform, Recursive filtering
  Deconvolution
  Edge detection (Canny, Deriche, etc.)
  Image descriptors (Haralick, Zernike, SIFT, MPEG-7)
  Steerable filters

PA172 Image Acquisition

zk 2/0 2 kr., podzim

• prof. RNDr. Michal Kozubek, Ph.D.
• Prerequisities: Knowledge at the level of the course PV131 Digital Image Processing is desirable.
• Goals: In this course, the student will learn about theoretical and practical aspects of the acquisition of image data and its transformation into digital form. The focus will be on optical systems that are the most common. Particular attention is paid to the acquisition of multidimensional information. The student will gain the basic understanding of both hardware of specific detectors and transport of the data from these sensors to computer memory and representation in computer memory. Based on the gained knowledge the student will be able to choose appropriate detector for a particular application and set suitable acquisition parameters.
• Learning outcomes: The student will be able to:
  formulate basic principles of digital image acquisition;
  describe characteristics of the most common imaging instruments;
  describe mutual interdependencies between the essential features of imaging instruments or settings;
  suggest suitable configurations for a given image acquisition task;
• Syllabus: Sources and detectors of light and other types of radiation.
  Cameras (CMOS, CCD, ICCD, EMCCD) and their properties, automatic focusing.
  Signal digitization and related protocols, norms and interfaces.
  Sources of noise and methods of its suppression.
  Optical system and its components, image formation in optical systems, microscopes and telescopes.
  Optical errors and their correction.
  Detection of multidimensional image data and principles of acquisition of spatial (3D), spectral and time-dependent information.
  Physical and optical cuts through the object, stereo-recording, measurement of topography (elevation) of the object surface, range imaging, tomographic approaches.
  Automation of image data acquisition.

PA173 Mathematical Morphology

zk 2/2 3 kr., jaro

• doc. RNDr. Petr Matula, Ph.D.
• Prerequisities: Knowledge at the level of course PV131 Digital Image Processing is useful.
• Goals: The objective of the course is to introduce mathematical morphology theory, algorithms, and applications to students interested in digital image processing.
• Learning outcomes: At the end of the course students should be able to: understand and explain the principles of mathematical morphology methods and efficient algorithms for their computation; respect their properties and theoretical limits; demonstrate their usage on typical image analysis problems in various application fields; solve image analysis problems using mathematical morphology.
• Syllabus: Structuring element and its decomposition
  Fundamental morphological operators (erosion, dilation, opening, closing, top-hat)
  Hit-or-miss transform, skeletons, thinning, thickening
  Geodesic transformations and metrics
  Morphological reconstructions
  Morphological filters
  Segmentation, watershed transform, markers, hierarchical segmentation
  Efficient implementation of morphological operators
  Granulometry, classification, texture analysis

PA174 Design of Digital Systems II

zk 2/0 2 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D. - prof. Ing. Václav Přenosil, CSc.
• Prerequisities: Course PB170 is recommended.
• Goals: The main aim of this course is to understand and master fundamental theoretical knowledge and practical virtuosity necessary for description and for design digital systems. The lessons are specialized in particular into the following topics:
  - logical algebra and function;
  - design of the combination circuits;
  - design of the sequential circuits;
  - structural components and cores of the digital systems.
• Learning outcomes: At the end of the course, students will be able to:
  - analyze the advanced digital system using logical algebra;
  - design kernel for digital systems.
• Syllabus: Encoding and data representation
  Logic algebra and optimization of the logical terms
  Implementation arithmetical and logical operations into computer machines
  Basic structural components of the digital systems
  Theoretical tools for design of the combination circuits
  Design of the combinational circuits
  Theoretical tools for design of the sequential circuits
  Design of the sequential circuits
  Basic operational units of the digital systems
  Operational principle and design of the basic digital systems units
  Hazards of the digital systems
  Digital systems cores
  Design systems and simulation of the digital systems

PA175 Digital Systems Diagnostics II

zk 2/0 2 kr., podzim

• prof. Ing. Václav Přenosil, CSc. - RNDr. Zdeněk Matěj, Ph.D.
• Prerequisities: Courses PA174 and PB170 od PB171 are recommended.
• Goals: The main aim of this course is to understand and master the fundamental theoretical pieces of knowledge of the technical system reliability theory. The lessons are specialized in particular into the following topics:
  - theory of the technical system's reliability,
  - theoretical and operative diagnostic of the digital systems,
  - reliability of the Man-Machine systems,
  - principles, models, and applications of the redundancy.
• Learning outcomes: Students will be able to reason about and design solutions relating to the reliability of embedded systems.
• Syllabus: Theory of the reliability
  Hardware and software reliability of the digital systems
  Definition of the reliability, classification of the failures
  Numerical parameters of the reliability
  Reliability evaluation of the electronics devices
  Grounding notations of theoretical and technical diagnostics
  Failures model of the technical systems
  Assembly methods of the combination and sequential logic circuits tests
  Fundamental procedures of the easily tested circuits
  Fundamental procedures of the fault-tolerant systems - checking of the failure-free activity, relaxation after failure, reconfiguration, depletion of the operation
  Methods and models of the redundancy
  Fundamental of the technical systems predicting diagnostics
  Hardware and software functionality checking tools of the digital system
  Hardware and software diagnostics tools of the digital systems
  Microprocessors systems testing and ROMBIOS

PA176 Architecture of Digital Systems II

zk 2/0 2 kr., jaro

• RNDr. Zdeněk Matěj, Ph.D. - prof. Ing. Václav Přenosil, CSc.
• Prerequisities: Course PV172 is recommended.
• Goals: The main aim of this course is to understand and master theoretical knowledge and practical virtuosity necessary for design high-performance digital systems. The lessons are specialized in particular into the following topics:
  - application of the modern design components;
  - the methodology of the modular systems;
  - connecting with external devices.
• Learning outcomes: At the end of the course, students will be able to:
  explain the principle of assembling powerful and functionally;
  reliable digital system structures;
  design a reliable digital system using contemporary design elements;
  work with external devices connected to digital systems;
  work with the MIPS instruction set;
• Syllabus: Digital computer main parts - sequencer
  Digital system structure
  Operational memory addressing methods
  Operational and CACHE memory structure, operation principles
  Microprocessor structure, Interruption system principles
  Direct memory access principles
  Digital processing chain
  Digital signal processing methods
  Signal spectra estimation methods
  Analog – digital converters
  Digital- analog converters
  Input – output devices
  Power supply unit, switch - mode power supply
  Primary power supply, battery, accumulators

PA179 Project Management

zk 1/1 2 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: No pre-requisities.
• Goals: The course focuses on:
• pre-project phases and project default settings
• project planning and resource allocation
• project risk management
• quality management
• phase of project termination
• process-oriented and competency-oriented PM techniques
• Learning outcomes: At the end of this course, students should be able to:
• distinguish between good and poor project management practice;
• understand most used PM standards and PM best practices;
• use the principles of selected PM techniques in practice;
• design a simple project and write its documentation;
• Syllabus:
• Introduction to PM
• PM life cycles
• Risk management
• Project modeling (WBS, Gantt)
• Network diagrams techniques (PERT, CPM)
• Project closure
Quality assurance
• Testing
• Inspections
• Metrics
• QA standards
Project management standards
• Process based (PMI Project Management Body of Knowledge, PRINCE 2)
• Competence based (IPMA Competence Baseline)
Examples from project management practice

PA180 Interim Project I+II

k 0/0 15 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: PV206 &&( PA179 || NOW ( PA179 ))&&((! PA185 )&&(!( NOW ( PA185 ))))&& SOUHLAS
  PV203 and PA181 and PA116 and PV207 and PA179.
• Goals: The goal is to complete an internship in a business on a job position that requires T-shaped skills.
• Learning outcomes: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: The Interim Project is based on taking up an internship in an organisation (company, state authority, etc.) with a focus in the area of study. The interim duration is 600 working hours, of which at least 300 will take place within the term's tuition period. Traineeship taken in AUTUMN term may start as early as July 1st, in SPRING term as early as January 1st of the pertinent year.
  The student's work in the course of the internship must comply with the T-shaped prifile, requiring both deep IT knowledge and experience and extensive overview and basic skills in other disciplines (economy, marketing, management, law etc.).
  The daily working shift will not exceed 8 hours.
  No contract between the Faculty and the organisation is required.
  While students may also choose from the offer published at the document server or from our partner companies (https://www.fi.muni.cz/for-partners/partners.html.en), it is up them to arrange their internship independently.
  Students must make sure the company guarantor meets the stipulated criteria, i.e. completed university education in a technical field with at least three years of experience in the area of the internship. The guarantor’s experience is calculated as of their university graduation.
  Student has a possibility to choose a business partner from a set of partners contracted by faculty for interim project accomplishment.
  Students must complete their entire Interim Project in one organisation. Exceptions are only possible with the lecturer’s consent. In case there is a threat of conflict of interests, the teacher may choose not to approve the course registration.
  IMPORTANT: As an essential precondition for approval of the registration/enrolment of the course the student must deliver signed Interim Proposal. Student will deliver the signed paper five days before enrolment at the latest to the course's Study Materials internship, specifically file: "Interim Proposal".
  At the beginning of the term (deadline to be specified by the lecturer) students will provide an Internship Acceptance Protocol. Students will deliver the Acceptance Protocol bearing signatures of the student and the company guarantor using the Homework Vaults.
  In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer).
  The students will file the Technical Report via IS ten days before the end of the course (in the form of an interview), while presentation and Confirmation of Completion must be uploaded three days before the end of the course. The lecturer will announce dates for final interviews with students that provide basis for final assessment.
  Should you have any questions, contact administrator Alena Hooperová by email.

PA180 Interim Project I+II

k 0/0 15 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D. - Bc. Alena Hooperová
• Prerequisities: PV206 &&( PA179 || NOW ( PA179 ))&&((! PA185 )&&(!( NOW ( PA185 ))))&& SOUHLAS
  PV203 and PA181 and PA116 and PV207 and PA179.
• Goals: The goal is to complete an internship in a business on a job position that requires T-shaped skills.
• Learning outcomes: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: The Interim Project is based on taking up an internship in an organisation (company, state authority, etc.) with a focus in the area of study. The interim duration is 600 working hours, of which at least 300 will take place within the term's tuition period. Traineeship taken in AUTUMN term may start as early as July 1st, in SPRING term as early as January 1st of the pertinent year.
  The student's work in the course of the internship must comply with the T-shaped prifile, requiring both deep IT knowledge and experience and extensive overview and basic skills in other disciplines (economy, marketing, management, law etc.).
  The daily working shift will not exceed 8 hours.
  No contract between the Faculty and the organisation is required.
  While students may also choose from the offer published at the document server or from our partner companies (https://www.fi.muni.cz/for-partners/partners.html.en), it is up them to arrange their internship independently.
  Students must make sure the company guarantor meets the stipulated criteria, i.e. completed university education in a technical field with at least three years of experience in the area of the internship. The guarantor’s experience is calculated as of their university graduation.
  Student has a possibility to choose a business partner from a set of partners contracted by faculty for interim project accomplishment.
  Students must complete their entire Interim Project in one organisation. Exceptions are only possible with the lecturer’s consent. In case there is a threat of conflict of interests, the teacher may choose not to approve the course registration.
  IMPORTANT: As an essential precondition for approval of the registration/enrolment of the course the student must deliver signed Interim Proposal. Student will deliver the signed paper five days before enrolment at the latest to the course's Study Materials internship, specifically file: "Interim Proposal".
  At the beginning of the term (deadline to be specified by the lecturer) students will provide an Internship Acceptance Protocol. Students will deliver the Acceptance Protocol bearing signatures of the student and the company guarantor using the Homework Vaults.
  In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer).
  The students will file the Technical Report via IS ten days before the end of the course (in the form of an interview), while presentation and Confirmation of Completion must be uploaded three days before the end of the course. The lecturer will announce dates for final interviews with students that provide basis for final assessment.
  Should you have any questions, contact administrator Alena Hooperová by email.

PA181 Services - Systems, Modeling and Execution

k 0/1 3 kr., jaro

• Ing. Leonard Walletzký, Ph.D. - doc. Mouzhi Ge, Ph.D.
• Prerequisities: Domain Understanding and Modeling
  Introduction to Service Science
• Goals: Practical seminars on the design of Service Systems applications. The aim of the course is to present how to design and prepare practical applications that meet requirements of Service Systems in comlex service environment. Course is organized in seminar form and relatively high level of student's team autonomy is expected.
• Learning outcomes: At the end of the course students should be able to: make reasoned decisions about service system design and service system innovation; work with information in given business domain; formulate value propositions.
• Syllabus: Service Systems Basics & Service Systems Engineering & Application as Service System & Application as Part of Service System & Application Domain Understanding & Application Domain Conceptual Modeling & Use Cases Analysis and Design & Application Goals Specification & Business Models Preparation & Service System Assembly, Production and Services Execution & Service system verification and validation & Finding application fields for new technologies & Service system design as a project or program & Service execution as a project within a portfolio

PA182 Managing in Reality

k 2/0 2 kr., podzim

• Tomas Gersl - David Michael Louis Moore - Ing. Leonard Walletzký, Ph.D.
• Prerequisities: SOUHLAS
  
• Goals: In this module you will learn about the key areas that apply to day to day leadership and management of an outsourced delivery organization, focussing on theory and interactive learning topics that will prepare you for "managing in reality"
• Learning outcomes: At the end of the course students should be able to: understand and explain what means leadership; work with information on processes in reality; create plans; make reasoned decisions about real business situations;
• Syllabus: This is an interactive course led by two Senior Managers from IT Outsourcing industry, that not only focuses on theory, but "Managing in Reality" - taking theory and relating to real life business cases.
  Identify the essentials for successful business management - the focus needed, and the skills in balancing customer, employee and business
  Learn about what happens on a daily basis in a delivery organization and the skills that are needed to achieve success
  Learn how a large corporation and how you can balance the needs of the people, how to motivate, develop and retain staff
  Go in depth on how to set goals, and how to measure them to meet and exceed business and customer expectation
  Understand that People are key to the success of the business - find out what you need to know, and what will help you and your teams succeed
  Have the opportunity to raise questions to members of a Senior Management Team, to be able to better understand what are learning contributes to your personal success.

PA183 Project in Systems Biology

k 0/0 2 kr., podzim

• doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
• Goals: At the end of the course students should be able to:
  search in public databases of biological knowledge;
  create an in silico model of a biological system;
  apply methods of computational systems biology to model analysis;
  predict hypotheses regarding emergent properties of the modeled biological system.
• Learning outcomes: At the end of the course students should be able to:
  use public databases of biological knowledge;
  construct an in silico model of a biological system;
  apply methods of computational systems biology to model analysis;
  infer hypotheses regarding emergent properties of the modeled biological system.
• Syllabus: Overview of key notions
  Setting of project topics
  Project realization
  Final student presentation

PA185 Interim Project I

z 0/0 8 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: PV206 &&( PA179 || NOW ( PA179 ))&&((! PA180 )&&(!( NOW ( PA180 ))))&& SOUHLAS
  PV203 and PA181 and PA116 and PV207 and PA179.
• Goals: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: Business oriented or more research oriented alternative can be chosen.
  This is the research oriented alternative - first part.
  The Interim Project is based on taking an internship in an organisation (company, state authority etc.) with focus in the area of study. The student's work in the course of the internship must comply with the T-shaped prifile, requiring both deep IT knowledge and experience and extensive overview and basic skills in other disciplines (economy, management, law etc.).
  Interim duration is 300 working hours of which at least 150 hours within the tuition period. Daily working shift will not exceed 8 hours.
  While students may choose from the offer published at the document server, it is up them to arrange their internship independently.
  Students must make sure the company guarantor meets stipulated criteria, i.e. completed university education in technical field with three years of experience in the area of the internship in the least. The guarantor’s experience is calculated as of their university graduation.
  PA185 is the first part of the internship to be followed up by PA186 in the same organisation in subsequent term. Exceptions are only possible with the lecturer’s consent.
  As an essential precondition for approval of the registration/enrolment of the course the student must deliver signed Internship Proposal. Student will deliver the signed paper five days before registration in the least to the internship coordinator email: hooperova.muni.cz.
  At the beginning of the term (deadline to be specified by the lecturer) students will provide Internship Acceptance Protocol. Students will deliver the Acceptance Protocol bearing signatures of the student and the company guarantor using the Homework Vaults.
  In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer). The students will file Technical Report and Confirmation of Completion via IS during the examination period.

PA185 Interim Project I

z 0/0 8 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D. - Bc. Alena Hooperová
• Prerequisities: PV206 &&( PA179 || NOW ( PA179 ))&&((! PA180 )&&(!( NOW ( PA180 ))))&& SOUHLAS
  PV203 and PA181 and PA116 and PV207 and PA179.
• Goals: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: Business oriented or more research oriented alternative can be chosen.
  This is the research oriented alternative - first part.
  The Interim Project is based on taking an internship in an organisation (company, state authority etc.) with focus in the area of study. The student's work in the course of the internship must comply with the T-shaped profile, requiring both deep IT knowledge and experience and extensive overview and basic skills in other disciplines (economy, marketing, management, law etc.).
  PA185 internship duration is 300 working hours of which at least 150 hours within the term's tuition period. Traineeship taken in AUTUMN term may start as early as July 1st, in SPRING term as early as January 1st of the pertinent year.
  Daily working shift will not exceed 8 hours.
  While students may choose from the offer published at the document server or from the Faculty's Industrial Partners, it is up them to arrange their internship independently. Students must make sure the company guarantor meets stipulated criteria, i.e. completed university education in technical field with three years of experience in the area of the internship in the least. The guarantor’s experience is calculated as of their university graduation.
  PA185 is the first part of the internship to be followed up by PA186 in the same organisation in subsequent term. Exceptions are only possible with the lecturer’s consent. In case there is a threat of conflict of interests, the lecturer may choose not to approve the enrolment.
  IMPORTANT: As an essential precondition for approval (do not forget to apply for approval in the IS) of the registration/enrolment of the course, the student must deliver signed Interim Proposal. Student will deliver the signed paper five days before enrolment at the latest to the course's Study Materials internship, file: "Interim Proposal".
  At the beginning of the term (deadline to be specified by the lecturer) students will provide Internship Acceptance Protocol. Students will deliver the Acceptance Protocol bearing signatures of the student and the company guarantor using the Homework Vaults. In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer).
  The students will file Technical Report and Confirmation of Completion via IS during the examination period.

PA186 Interim Project II

k 0/0 7 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: PA185 && SOUHLAS
  Strictly after PA185
• Goals: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: Business oriented or more research oriented alternative can be chosen.
  This is the research oriented alternative - second part.
  The Interim Project is based on taking an internship in an organisation (company, state authority etc.) with focus in the area of study. Interim duration is 300 working hours of which at least 160 take place within the tuition period. Daily working shift will not exceed 8 hours.
  Student continues their internship in the same organisation as PA185 whilst the company guarantor should remain the same as in PA185.
  PA186 is the second half of the internship that continues in the same organisation as PA185 in the subsequent term. Exceptions are only possible with the lecturer’s consent.
  Previous completion of PA185 is an essential precondition for approval of the registration/enrolment of PA186.
  In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer). The students will file Technical Report via IS ten days before the end of the course, while presentation and Confirmation of Completion (of PA186) must be uploaded three days before the end of the course.
  In the examination period, the lecturer will announce dates for final interviews with students that provide basis for final assessment.

PA186 Interim Project II

k 0/0 7 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D. - Bc. Alena Hooperová
• Prerequisities: PA185 && SOUHLAS
  Strictly after PA185
• Goals: At the end of the course students should be able to work on a junior level position in a service oriented company.
• Syllabus: Business oriented or more research oriented alternative can be chosen.
  This is the research oriented alternative - second part.
  The Interim Project is based on taking an internship in an organisation (company, state authority etc.) with focus in the area of study. Interim duration is 300 working hours of which at least 160 take place within the tuition period. Daily working shift will not exceed 8 hours.
  Student continues their internship in the same organisation as PA185 whilst the company guarantor should remain the same as in PA185. PA186 is the second half of the internship that continues in the same organisation as PA185 in the subsequent term. Exceptions are only possible with the lecturer’s consent.
  Previous completion of PA185 is an essential precondition for approval of the registration/enrolment of PA186.
  In the course of the term students will deliver the interim report electronically using the Homework Vaults (deadline to be specified by the lecturer). The students will file Technical Report via IS ten days before the end of the course, while presentation and Confirmation of Completion (of PA186) must be uploaded three days before the end of the course.
  In the examination period, the lecturer will announce dates for final interviews with students that provide basis for final assessment.

PA190 Digital Signal Processing

zk 2/0 2 kr., jaro

• prof. Ing. Karel Hájek, CSc. - prof. Ing. Václav Přenosil, CSc.
• Prerequisities: The PA174 course or at least the PB170 course is suitable for successful completion this course.
• Goals: To introduce the fundamentals of digital signal processing and related applications. This course will cover linear system analysis, z-transform, discrete Fourier transform (DFT) and its applications, FFT algorithms, digital filter (FIR and IIR) design and multi-rate signal processing.
• Learning outcomes: Students will:
  understand principles of digital signal processing
  be able to design algorithms to process signals
  understand the way Fourier transformation is used to process signals.
• Syllabus: 1) An Introduction to digital signal processing (DSP), signals and their types
  2) Continuous and discrete-time signals, their spectrum, analog-to-digital and digital-to-analog conversion, sampling theorem
  3) Analog signals, analog systems, discrete-time signals, discrete-time systems, analysis of discrete-time LTI systems, correlation of discrete-time signals
  4) Z-transform, properties of the Z-transform, rational z-transforms, inversion of the Z-transform, analysis of LTI systems in the z-domain
  5) Frequency-analysis of continuous-time signals, frequency analysis of discrete-time signals, properties of the Fourier transform for discrete-time signals, frequency-domain characteristics of LTI systems
  6) Frequency-domain sampling: The DFT, properties of the DFT, Linear-filtering methods based on the DFT, frequency analysis of signals using the DFT
  7) Efficient computation of the DFT: FFT algorithms
  8) Estimating the frequency of the dominant harmonic signal
  9) Basic principles of the digital filter realization as a discrete model of analog filtering
  10) Structures for the realizations of discrete-time systems, structures for FIR systems, structures for IIR systems, quantization and round-off effects in digital filters
  11) Design of digital filters, design of FIR filters, design of IIR filters from analog filters, frequency transformations, design of filters based on least-squares method, design of FFT filtering
  12) Introduction of the MATLAB Signal Processing Toolbox

PA191 Advanced Computer Networking

zk 2/0 2 kr., podzim

• doc. RNDr. Eva Hladká, Ph.D.
• Prerequisities: ! PA159 && ! NOW ( PA159 )
  
• Goals: The main goal of this course is to provide a deeper insight into the area of computer networks (behind the level of basic bachelor courses) and to provide a complex survey of crucial protocols in computer networks (routing, IPv6, quality of service, etc.). Graduate will be able to analyze the behavior of even complex computer networks and propose their topology as well as solutions to particular problems. Graduate will also know the features and benefits of the IPv6 network protocol and become able to design and implement an IPv6 network. Graduate will obtain a survey of mechanisms used for ensuring the quality of service in computer networks. Graduate will be able to discover bottlenecks in communication systems and will be able to propose their removal/elimination. Graduate will learn the basic principles in the area of mobile networks, he or she will obtain an idea about their specific features from the perspective of computer networks. Graduate will be also able to prepare and lead simple courses targeted in particular areas of computer networks and their applications.
• Learning outcomes: Graduate will be able to analyze the behavior of even complex computer networks and propose their topology as well as solutions to particular problems.
  Graduate will also know the features and benefits of the IPv6 network protocol and become able to design and implement an IPv6 network.
  Graduate will obtain a survey of mechanisms used for ensuring the quality of service in computer networks.
  systems and will be able to propose their removal/elimination.
  Graduate will learn the basic principles in the area of mobile networks, he or she will obtain an idea about their specific features from the perspective of computer networks. Graduate will be able to discover bottlenecks in communication
• Syllabus: Architecture of computer networks, ISO/OSI and TCP/IP model, IP protocol, transport protocols (TCP, UDP), basic services of computer networks -- short recapitulation.
  Advanced features of IPv6 protocol: mobility and security, ICMPv6, IPv6 support in applications.
  Advanced routing mechanisms: distance vector, link state and path vector routing. Router architecture. Traffic Engineering. MPLS, MPLS labels' assignment and distribution, MPLS routing.
  Advanced TCP protocol features. Protocols for high bandwidth networks with high latency.
  Peer-to-peer networks. Basic architectures, routing in structured and unstructured P2P systems and hybrid P2P networks.
  Ad-hoc/sensor networks: history, types, data transmission principles, communication principles, routing, mechanisms for ensuring reliable communication, protocols, actual trends.
  Computer networks and multimedia: multimedia application demands, actual trends

PA192 Secure hardware-based system design

zk 2/2 5 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D. - prof. Ing. Václav Přenosil, CSc. - Mgr. Filip Roth
• Prerequisities: • Design of digital systems:
  - encoding and data representation,
  - logic algebra and optimization of the logical terms,
  - implementation arithmetical and logical operations into digital systems.
  
  • Architecture of digital systems:
  - operational memory addressing methods,
  - interruption system principles,
  - direct memory access principles,
  - input / output devices.
  
  • Digital systems dependability:
  - basics of probability theory and statistics.
• Goals: The course is focused on architectures of secure digital systems, to ensure reliability, dependability, and security of digital systems, assess and learn how to design safe and reliable digital systems. The course will present common problems and design of secure digital systems on real-world examples.
• Learning outcomes: Upon completion of this course, students will have an overview of the architecture of secure digital systems.
• Syllabus: 1) Design of the Digital Systems:
  i) design elements of digital systems,
  ii) design of the combinational circuits,
  iii) design of the sequential circuits.
  
  2) Design of the Digital Systems:
  i) digital systems cores,
  ii) design systems and simulation of the digital systems.
  
  3) Architecture of Digital Systems:
  i) overview of microcontrollers, programmable arrays and DSP,
  ii) a/d and d/a converters,
  iii) digital signal processing methods.
  
  4) Digital Systems Dependability:
  i) reliability evaluation of the electronics devices,
  ii) failures model of the technical systems,
  iii) methods and models of the redundancy,
  iv) Markov reliability and availability models.
  v) fault tolerant systems.
  
  5) Digital Systems Testing:
  i) design of test step,
  ii) design detection and localization tests,
  iii) fault-tolerant systems,
  iv) checking methods.
  
  6) Controls to manage the reuse of logic:
  i) implementing a state machine to direct data flow in case of more complex variations to the input of a resource.
  
  7) Sharing logic resources:
  i) different resources are shared across different functional boundaries.
  
  8) The impact of RESET:
  i) an improper reset strategy can create an unnecessarily large design or makes synthesis and optimization tools ineffective,
  ii) Design without RESET capability, design without SET capability, design without asynchronous RESET capability,
  iii) Impact of RAM RESET,
  iv) Optimization using set/reset pins for logic implementation.
  
  9) Protection of HW against reverse engineering.
  
  10) Hardware trojans, Side-channel attaches and countermeasures

PA193 Secure coding principles and practices

zk 2/2 5 kr., jaro

• doc. RNDr. Petr Švenda, Ph.D. - RNDr. Petr Ročkai, Ph.D.
• Prerequisities: Basic knowledge in applied cryptography and IT security, practical experience in programming with C/C++ language, basic knowledge in formal languages and compilers, user-level experience with Windows and Linux OS
• Goals: At the end of this course the student will understand what the typical security issues related to secure coding are. The student will also be able to design applications and write programs in C/C++ and Java in a more secure way.
• Learning outcomes: After a course completion, the student will be able to:
  - able to review source code for typical security bugs;
  - able to properly check and sanitize check program input data;
  - able to use standard tools for static and dynamic code analysis and interpret results;
  - able to describe typical bugs from concurrent program execution and write code without it;
  - able to apply systematic methods to produce code with better resiliency against bugs;
  - understand basic cryptographic primitives and their proper use in source code;
• Syllabus: Language level vulnerabilities, secure programming techniques and approaches, input processing, static and dynamic code checking, binary defenses and exploits, security testing, integrity of modules, concurrent issues, random number generation and usage, security primitives, security code review.

PA194 Introduction to Service Science

zk 2/0 2 kr., podzim

• doc. Mouzhi Ge, Ph.D. - Ing. Leonard Walletzký, Ph.D.
• Goals: The course is focused to the presentation of basic elements and contexts of the Service Science field. Withal it’s concept is built to understand the problem of Service Science in higher complex of circumstances – economics, social and particularly IT . The course emphasizes the role of IT in the field of services.
• Learning outcomes: Students will understand:
  - the basic of the Service Dominant Logic concept
  - the methodology of Service Thinking and Service Design
  - consequences related to assymetric information theory
  - examples of the application os service approach in IT domian
  - concepts of advanceds service modelling
• Syllabus: Introduction
  Goods and Service Dominant Logic
  Role of information in in GDL and SDL
  Service systems and imperfect information
  Service system
  Dual service system
  Dynamic service system
  IT in SDL
  Software as a Service
  Marketing concepts in SDL
  Service Science, Management and Engineering

PA195 NoSQL Databases

k 2/1 3 kr., podzim

• doc. RNDr. Vlastislav Dohnal, Ph.D.
• Prerequisities: PB154
  
• Goals: The course covers: 1) the principles behind the NoSQL databases, such as chapters from modern distributed database theory, P2P indexing or the MapReduce programming model; 2) architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases); 3) detailed description of selected NoSQL database systems including practical experience; 4) other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.)
• Learning outcomes: After the course, students will:
  - understand the principles behind the NoSQL databases;
  - know architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases);
  - know in detail several selected NoSQL database systems including practical experience;
  - know about other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.)
• Syllabus: Why NoSQL, Principles, Taxonomy.
  Distribution Models, Consistency in Distributed Databases.
  MapReduce + Hadoop.
  Key-Value Stores, practical experience with Riak & Infinispan.
  Document Databases, practical experience with MongoDB & PostgreSQL.
  Column-family Stores, practical experience with Cassandra.
  Graph Databases, practical experience with Neo4J.
  Other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.).

PA196 Pattern Recognition

zk 2/2 3 kr., podzim

• doc. Ing. Vlad Popovici, PhD
• Prerequisities: At least working knowledge of statistics/probabilities, linear algebra and mathematical analysis are required
• Goals: By successful completion of the course, the students will: (i) have solid understanding of the principles of pattern recognition; (ii) master the main methods for model performance estimation; (iii) have a good grasp of different parametric and non-parametric methods for classification; (iv) understand the main classification methods; (v) have a working knowledge of kernel methods; (vi) understand and master the performance estimation techniques (vii) have hands-on experience of using pattern recognition methods in computer vision and biomedical applications.
• Learning outcomes: By successful completion of the course, the students will: (i) have solid understanding of the principles of pattern recognition; (ii) master the main methods for model performance estimation; (iii) have a good grasp of different parametric and non-parametric methods for classification; (iv) understand the main classification methods; (v) have a working knowledge of kernel methods; (vi) understand and master the performance estimation techniques (vii) have hands-on experience of using pattern recognition methods in computer vision and biomedical applications.
• Syllabus: 1. Introduction: problem setting; distances, metrics, similarity; Bayesian decision theory 2. Non-parametric methods: density estimation; nearest neighbor methods 3. Classification performance: performance criteria; performance estimation; confidence intervals; classifier comparison 4. Linear discriminants: decision surfaces; parameter optimization; shrinkage, penalized regression, optimal separating hyperplanes; SVM 5. Ensemble methods: fusion of labels or continuous outputs; parallel and cascaded systems; bagging and boosting; AdaBoost 6. One-class classifiers: Gaussian mixtures; support vector density estimators; outlier detection 7. Dimensionality reduction: feature selection; PCA, ICA, non linear PCA 8. Unsupervised learning/clustering: principles; mixture of densities; hierarchical clustering

PA197 Secure Network Design

zk 2/2 5 kr., jaro

• prof. RNDr. Luděk Matyska, CSc. - doc. RNDr. Eva Hladká, Ph.D. - Mgr. Marek Sýs, Ph.D. - doc. RNDr. Petr Švenda, Ph.D. - RNDr. Marek Kumpošt, Ph.D.
• Prerequisities: PA191 || PA159 || PA151
  Basic knowledge of computer networks. Basic knowledge in applied cryptography and IT security. User-level experience with Windows and Linux OS, ability to configure tools and/or interfaces. Practical experience in programming with imperative languages like C/C++ or Java.
• Goals: At the end of the course the students will be able to: understand the methods and technologies that are at the base of secure network design; design architecture of network; deploy securely sensor networks.
• Learning outcomes: At the end of the course the students will be able to: understand the methods and technologies that are at the base of secure network design; design architecture of network; deploy securely sensor networks.
• Syllabus: Basic design requirements and principles (basic network architecture and functions, general requirements on the security and reliability). Network specific faults, threats, and attacks. Security architectures (Secure and resilient routing, secure DNS, secure channels, trusted network access, resilient architectures). Operational security management – how to design and manage reliable networks. Network monitoring and defence mechanisms (firewalls, IDS, netflow). Penetration testing. WiFi networks and security. (Wireless) personal area networks. Wireless Sensor Networks (WSN). Cryptographic aspects of WSN.

PA199 Advanced Game Development

k 2/1 3 kr., jaro

• Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: The knowledge of computer graphics fundamentals
• Goals: This course intends to introduce advanced game design to the students. The course will cover all major aspects of game design such as advanced computer graphics, human computer interaction and game design issues.
• Learning outcomes: At the end of the course students will be able to: Demonstrate an understanding of the main mathematical concepts used in computer game design; Mathematically model all the components of an interactive computer game; Have a good understanding of the collision detection techniques that are used in computer games and apply them in practice; Design and implement an interactive computer game from scratch (i.e. not using a games engine).
• Syllabus: Introduction to advanced games design
  Game engine architectures
  Mathematics and physics for computer game design
  Collision detection techniques for computer games
  Fractal terrain generation
  City and road modeling
  Fluid modeling
  Deformation techniques for games
  Procedural texturing techniques
  Animation for computer games
  Crowd modeling techniques
  Online virtual environments
  Mobile game development
  Advanced interaction techniques
  Serious games

PA200 Cloud Computing

k 2/0 2 kr., jaro

• Ing. Ilya Etingof - Joao Grade - Mgr. Kamil Malinka, Ph.D.
• Prerequisities: PA018 || PA151 || PA159 || PA191 || PV017 || PV157
  
• Goals: The graduate of this course shall be able to: - understand virtualization and cloud computing technologies including virtual machines and containers - consider the trade-offs and pathways of cloud deployment and migration - be aware of the design, services and inner workings of a typical cloud system like OpenStack - deploy and maintain a cloud project - design applications for cloud environments
• Learning outcomes: Graguate of this course shall be able to:
  - understand basic concepts of cloud computing technologies and infrastructure
  - select appropriate methods for design and practical deployment of cloud systems and applications
• Syllabus: 1. Overview of Cloud Computing
  2. Cloud Service Delivery Models
  3. Virtualization technologies – VMs and Containers
  4. Cloud Deployment Scenarios
  5. Transition & Migration to a cloud computing environment
  6. Overview of contemporary cloud service providers
  7. Introduction to OpenStack - history, design, and development
  8. OpenStack cloud administration and cloud software development
  9. Containers, orchestration software and clouds
  10. Cloud infrastructure – data repositories
  11. Scientific clouds - distributed computing and data storage infrastructure
  12. Cloud Security - Security in Cloud Computing
  13. Auditing / logging
  14. Future Development – Next Generation Cloud

PA212 Advanced Search Techniques for Large Scale Data Analytics

zk 2/0 2 kr., jaro

• RNDr. Jan Sedmidubský, Ph.D. - prof. Ing. Pavel Zezula, CSc.
• Prerequisities: Knowledge of the basic principles of data processing is assumed.
• Goals: The objective of the course is to explain the problems of information retrieval in large collections of unstructured data, such as text documents or multimedia objects. The main emphasis will be given on describing basic principles of distributed algorithms for processing large volumes of data, e.g., Locality-sensitive hashing, MapReduce or PageRank. The algorithms for processing stream data will be introduced as well. The students will also acquire practical experience by applying the presented algorithms to the specific tasks.
• Learning outcomes: After completing the course students are able to:
  - Describe algorithmic-based differences between processing offline data collections and online data streams; - Understand the basic principles of distributed algorithms for processing large volumes of data;
  - Evaluate the results of algorithms by several metrics;
  - Apply presented algorithms, such as K-Means, Locality-sensitive hashing, MapReduce or PageRank, to the specific tasks.
• Syllabus:
• Introduction – What is searching, Things useful to know
• Support for Distributed Processing – Distributed file system, MapReduce, Algorithms using MapReduce, Cost model and performance evaluation
• Retrieval Operators and Result Evaluations – Common similarity search operators, Retrieval metrics
• Clustering – K-means algorithms, Clustering in non-Euclidean spaces, Clustering for streams and parallelism
• Finding Frequent Item Sets – Handling large datasets in main memory, Counting frequent items in a stream
• Finding Similar Items – Applications of near-neighbor search, Shingling of documents, Similarity-preserving summaries of sets, Locality sensitive hashing
• Searching in Data Streams – The stream data model, Filtering streams
• Link Analysis – Page Rank, Topic sensitive, Link spam
• Search Applications – Advertising on the web, Recommendation systems (collaborative filtering), Mining social-network graphs

PA213 Advanced Computer Graphics

zk 2/0 2 kr., jaro

• doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: Basic algebra and geometry. The knowledge of computer graphics fundamentals.
• Goals: Lectures cover classical and the most important fields of interest in computer graphics. These are compared with current research results. Students should gain the purview of the key issues and research trends in computer graphics field.
• Learning outcomes: At the end of the course students
  - will understand the theoretical concepts of modern computer graphics;
  - will be able to judge and evaluate the research and development trends in the field;
  - will be able to asses the complexity of computer graphics algorithms;
  - will be able to design complex graphics systems in various application areas.
• Syllabus: Global illumination
  Sampling and reconstruction
  Rendering equation and its solution
  Radiosity method
  Monte Carlo and path tracing
  Photon mapping
  Participating media
  BSSRDF models
  Image-based rendering
  Image Warping
  Image-based modelling and rendering
  The light field
  Direct rendering of volume data
  Terrain rendering
  Point-based rendering
  Matting
  Collision detection
  Forward Kinematics, Inverse Kinematics
  All topics are explained with both mathematical description as well as its algorithmic counterpart. Students will learn theoretical basis of the above-described concepts, algorithms, and representations.

PA214 Visualization II

zk 2/0 3 kr., jaro

• doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: PV251
  Knowledge of basic visualization principles and techniques, taught in the PV251 Visualization I course.
• Goals: The course should extend the knowledge of students in visualization and its specific usage in different domains. The students will understand the principles of the main visualization disciplines - information visualization, scientific visualization, and visual analysis. These will be demonstrated on real application scenarios from different fields - medical, molecular, environmental visualization, etc.
  By presenting and analyzing the latest papers in this field, the students will obtain a solid overview of the current research topics in visualization.
• Learning outcomes: - Knowledge of the principles of information visualization, scientific visualization, and visual analysis
  - Overview of the application domains and domain-specific tasks and problems, capability to analyze these problems
  - Understanding research papers in visualization
  - Capability to complete own visualization project - from initial data and problem analysis to the design of a solution and final implementation.
• Syllabus: Visualization - main topics and challenges (summarizing the basic information about visualization)
  Visualization process - from analysis and design to realization
  Information visualization principles and examples
  Scientific visualization principles and examples
  Visual analysis (VA) principles and examples
  Medical and molecular visualization and VA
  Environmental and geovisualization and VA
  Volumetric visualization and VA

PA215 Game Design I

zk 2/0 2 kr., podzim

• Mgr. et Mgr. Zdeněk Záhora - Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: The course is designed for beginners, although the rich knowledge of (digital) games is considered to be an advantage.
• Goals: The aim of the Game Design I. course is to (a) develop the ability to critically analyse digital and board game rules and structure and (b) to teach students practical methods of rapid paper prototyping of gaming systems. These two building blocks support the main objective of the course which is (c) to improve students skill in designing games.
• Learning outcomes: Student will be able to:
  - design simple games
  - create paper game prototypes
  - analyze and change rules of (digital) games
  - understand game design processes in game development environments
  - determine the type of target player and perceive the differences between the different experiences that games can stimulate
  - design and perform tests to verify game qualities for the target audience
  - to describe the creative possibilities of (non) digital games as a unique medium, i.e. as both a technology and a creative instrument.
  
  Course outcome:
  - 1x text: analysis of a specific digital game | solo work
  - 1x design: digital game design | solo work
  - 2x game: board game prototype | teamwork
• Syllabus: 00 WORKSHOP | BoardGameDesign (one of the weeks during the course - operationally)
  01 Introduction | Games and game design
  02 Game vs Game Designer vs Player
  03 Creative Process| Fundamentals of Game Design | Player
  04 Rules | Goals
  05 Game vs. Play vs Gameplay | vs Toy vs Puzzle
  06 Core Mechanics
  07 Game Balancing
  08 Playtesting
  09 Advanced design objectives | Level design | Narrative design | Experience design | Physiological responses
  10 The conclusion of the course | BoardGameJam

PA216 Game Design II

zk 2/0 2 kr., jaro

• Mgr. et Mgr. Zdeněk Záhora - Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: PA215
  The course builds on the PA215 Game Design I. If needed, permission may be considered but only after prior personal consultation and debate over the content of the previous course.
• Goals: The aim of Game Design II. is to (a) enhance the knowledge and applied the use of (digital) games language, (b) analyze complex design techniques and specific features of digital games, and (c) develop the ability to connect individual elements of (digital) games to interrelated dependencies.
  The main objective of the course is (d) to train and develop students skills in designing games.
• Learning outcomes: Student will be able to:
  - design more complex games
  - understand the complex interdependence of game elements
  - analyze and change the overall gaming experience of (digital) games
  - understand and explain advanced game design practices
  - based on design documentation to detect contradictions in the design and to prevent potential production barriers
  - better understand player experience and test design hypotheses on a group of players
  
  Course outcome:
  - 1x text: review of the game design publication | solo work
  - 1x design: digital game design | solo work
  - 1x play: polished board game ready for the release | teamwork
  - 1x game: digital game prototype | teamwork
• Syllabus: 00 WORKSHOP - GameDesignChallenge (one of the weeks during the course - operationally)
  01 Game design ontology
  02 Semiotics and abstract analysis in games
  03 Emergent systems and gameplay
  04 Randomness and probability
  05 Adaptive difficulty, game balancing and accessibility
  06 Pleasure, boredom, anxiety, challenge
  07 Decisions
  08 Game world and Player character
  09 Games as narrative medium
  10 From cheats to modifications and (fan) communities
  11 Designing metagame

PA217 Artificial Intelligence for Computer Games

zk 2/0 2 kr., jaro

• doc. Mgr. Hana Rudová, Ph.D.
• Prerequisities: PV255 || SOUHLAS
  Base knowledge of Unity is required. If PV255 not successfully passed, the student must demonstrate a representative set of projects solved in Unity. Based on that, course enrollment is confirmed or not. The projects should be sent to the teacher by the beginning of the semester (or in the first week of the semester).
• Goals: The course provides information about methods from artificial intelligence used for the development of computer games. Students will learn about data structures and algorithms from artificial intelligence needed for movement, pathfinding, decision making for a single character, strategy and tactics. Students will have practical experience with AI programming.
• Learning outcomes: The graduate will be able to apply proper algorithms and approaches from artificial intelligence in computer games.
  The graduate will be aware of how to implement artificial intelligence algorithms in the game engine by coding in Unity.
• Syllabus: Introduction and history.
  Movement: kinematic movement, steering behaviors, combining steering behaviors.
  Search and pathfinding: introduction to search algorithms, A* data structures and heuristics, world representation, hierarchical pathfinding.
  Decision making for a single character: decision trees, state machines, behavior trees, fuzzy logic, Markov systems, goal-oriented behavior, rule-based systems, blackboard architectures, action execution.
  Strategy and tactics: tactical waypoints, tactical analyses, tactical pathfinding, coordinated action.
  Board games: minimaxing, transposition tables, Monte Carlo search.
  Implementation of AI algorithms in Unity.

PA218 Internship - Computer Games

z 0/0 12 kr., podzim

• Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: souhlas
  Serious interest in digital games development area. At least one realized digital game project (e. g. in a scope of PV255 and PV266). Mutual agreement between student, lector and mentor.
• Goals: Internship at a digital game development company. The main goal is to gain experience with work on the real game project in the scope of a large game studio. At the end of the course, a student should be able to work in a junior level position in a game development company.
• Learning outcomes: At the end of the semester, a student should be able to:
  - Identify and describe roles in the development team and their mutual interactions;
  - Effectively use tools for team communication and collaboration;
  - describe the workflow in a larger team, apply it in new projects;
  - Work on digital game development in the scope of a larger team;
• Syllabus: Semestral internship in the game development company.
  Before the beginning internship a mentor, student’s role in the team and the game project will be specified based on mutual agreement.
  During the internship, a student will be working on the specified project led by given mentor.
  Regular meetings on project progress will be organized including the student, the lector and the mentor.

PA220 Database systems for data analytics

zk 2/0 2 kr., podzim

• doc. RNDr. Vlastislav Dohnal, Ph.D.
• Prerequisities: Knowledge of relational database systems, query and transaction processing and principles of query optimization, preferably in the scope of PA152 course.
• Goals: To get acquainted with the possibilities of database systems and their use for data analytics: design and implementation of data warehouses; query languages and tools for integration with external computing and analytics platforms (Apache Hive); analytical databases (Apache Impala).
• Learning outcomes: Student will be able to: - understand the principles of data warehouses; - describe typical examples of data warehouse use-cases; - design a data warehouse; - create a solution to analytical tasks.
• Syllabus: Introduction to data warehouses and business intelligence.
  Data modeling for data warehouses: dimensions, facts.
  Data warehouse lifecycle.
  Data warehouse creation processes: ETL.
  Data warehouse applications: sales, CRM.
  Analytical databases.
  Languages for analytical tasks.
  Big data analytics.

PA221 Hardware description languages

k 0/2 3 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D.
• Prerequisities: Course PV200 is recommended.
• Goals: Within this course the students will obtain deeper knowledge on the field of programmable structures (e.g. FPGAs) and SoC (System on Chip) and get familiar with advanced methods of hardware design using hardware description languages. VHDL is used to demonstrate most of the principles.
• Learning outcomes: Graduates of this course will be able to:
  - understand advanced FPGA principles;
  - understand the programming language VHDL;
  - design systems with SoC;
  - program application for SoC.
• Syllabus: • VHDL – concepts, basic syntax, abstraction levels, design hierarchy
  • desig with SoC FPGA in VHDL or Verilog
  • FPGA design - high speed design, best practice
  • prefabricated components – IP cores, Megafunctions
  • ethernet with FPGA
  • sofcore computing – NIOS2 processor system
  • PCB design for FPGA
  • practical tasks in Quartus II suite.

PV003 Relational Database System Architecture

zk 2/1 3 kr., jaro

• RNDr. Milan Drášil, CSc.
• Goals: The course is focused on an architecture of relational database engines and the SQL query language.
• Learning outcomes: Student will be able to fully comprehend usage of SQL query language.
• Syllabus: A brief history of relational databases, independent data store, advantages and disadvantages.
  Relational algebra, requirements to communication and query language.
  Parts of SQL language (definition, manipulation, transaction), lexical conventions of SQL.
  Data Definition Language, creation and modification of tables, sequence definition, dropping an object from data scheme.
  Integrity constraints, definition in SQL.
  An effective approach to table rows, indexes.
  Data Manipulation Language, insert, delete, update rows in table, foreign keys context.
  Join of tables, outer join, processing techniques of join.
  WHERE clause construction, aggregation functions
  Hierarchical queries
  Set operations.
  VIEWs a MATERIALIZED VIEWs.
  Object relational database, methods, abstract types, inheritance.
  XML data interface to objects.
  Execution plan, query tuning, HINT phrase.
  Transaction control, isolation levels, SELECT query and transactions, deadlock and its detection.
  Procedural languages in relational databases, procedures and functions, packages, deterministic functions, triggers.
  Normal forms and data schemes in relational databases.

PV004 UNIX

zk 2/0 2 kr., jaro

• doc. Ing. Michal Brandejs, CSc.
• Goals: The students of this course will be introduced to the general principles of the UNIX operation system. At the end of this course, students should know the Shell and should be able to program shell scripts.
• Learning outcomes: At the end of this course, the student will understand the principles of the UNIX operating system, will be able to control the unix shell line interface on a common user level, program simple shell scripts, and manage manipulation of text files, including understanding the use of regular expressions.
• Syllabus: UNIX history, main features, system access.
  System structure: file systems, processes.
  Access rights.
  User interface: shell and its programming.
  Text processing: regular expressions, editors, text processing commands.
  Setting of the user environment.
  Multi-user communication, status of the system.

PV005 Computer Network Services

z 2/0 2 kr., podzim

• doc. Ing. Michal Brandejs, CSc. - RNDr. Jan Kasprzak, Ph.D. - RNDr. Tomáš Obšívač
• Goals: This course provides an introduction to the computer networks questions as far as both technical aspects and software aspects are concerned. The students will be also acquainted with basic provided services.
• Learning outcomes: At the end of this course the student will be able to orientate in technologies available to students at the Faculty of Informatics, will understand basic principles of computer networks and basic network services.
• Syllabus: TCP/IP Networks: architecture, addressing, routing, BIND.
  Network services under TCP/IP: telnet/rlogin, ftp/rcp.
  E-mail: RFC 822, MIME, system architecture.
  WWW: URL, httpd, clients.
  WWW server. http protocol.
  Secure communication: ssh, SSL, https etc.
  Introduction to JavaScript.
  Local area networks media.

PV017 Information Technology Security

zk 2/0 2 kr., podzim

• doc. Ing. Jan Staudek, CSc.
• Prerequisities: PV080 course should be passed before this course.
• Goals: At the end of the course students should be able
  evolve information security policy,
  elaborate risk analysis,
  assess adjusted level of information security guaranty,
  justify measurements and controls options and
  explain information security issues on the level of management of institution
• Learning outcomes: Students completing this course will be able to fulfill the role of manager of information security
• Syllabus: Concepts, definitions
  Anatomy of information security
  Standardization process
  Information security management in an organization
  Steering response to security incidents
  Risk management
  Information security policy
  Information security management system, ISMS, ISMS project
  Measurement and digital evidence
  Audit and evaluation of information security

PV019 Geographical Information Systems

zk 2/0 2 kr., podzim

• RNDr. Milan Drášil, CSc.
• Prerequisities: ! PA049
  The prerequisities for this course are: basic skills in relational databases, sorting/searching techniques, base analysis (calculus) course and the knowledges of analytical geometry (a secondary school level).
• Goals: The course is focused to core technologies used for a GIS servers, as well as for GIS client applications development. The course is practically oriented, techniques are illustrated by examples.
• Learning outcomes: Student will understand core technologies used for a GIS servers, as well as for GIS client applications development.
• Syllabus: Coordinate systems, cartographic projections and transformation methods.
  Traditional maps, GIS data sources.
  Spatial data types, hierarchy and spatial relations.
  Data stores for spatial data.
  An effective spatial searching, the problem definition, the static and the dynamic problem variant.
  Traditional approach to space indexing, Grid - method and its RDBMS implementation, Quad-tree for points.
  kD-trees, how to index a space and balancing possibilities.
  Non-pointer Quad-tree, spatial query decomposition.
  SB+ trees and spatial interaction queries.
  R-trees, node splitting heuristics in linear and quadratic complexity.
  Manipulation operations over geometric objects.
  Validation functions over geometric objects.
  Set operations over geometric objects.
  Raster data and its sources.
  Quantitative properties of raster data.
  Linear filtration ant its application in GIS.
  Geometric transformations of raster maps.
  Vector and raster mutual conversions.

PV021 Neural Networks

zk 2/0 4 kr., podzim

• doc. RNDr. Tomáš Brázdil, Ph.D.
• Prerequisities: Recommended: knowledge corresponding to the courses MB102 and MB103.
• Goals: Introduction to neural networks.
• Learning outcomes: At the end of the course student will have a comprehensive knowledge of neural networks and related areas of machine learning. Will be able to independently learn and explain neural networks problems. Will be able to solve practical problems using neural networks techniques, both independently and as a part of a team. Will be able to critically interpret third party neural-networks based solutions.
• Syllabus: Basics of machine learning and pattern recognition: classification and regression problems; cluster analysis; supervised and unsupervised learning; simple examples
  
  Perceptron: biological motivation; geometry
  
  Linear models: least squares (pseudoinverse, gradient descent, Widrow-Hoff rule); connection with Bayes classifier; connection with maximum likelihood; regularization; bias-variance decomposition
  
  Multilayer neural networks: multilayer perceptron; loss functions; backpropagation
  
  Practical considerations: basic data preparation; practical techniques for improving backpropagation; bias & variance tradeoff; overfitting; feature selection; applications
  
  Hopfield network: Hebb's rule; energy; capacity
  
  Deep learning: restricted Boltzmann machines (sampling, maximum-likelihood learning, contrastive divergence learning); learning in deep neural networks (vanishing gradient, pretraining with autoencoders, deep belief networks)
  
  Convolutional networks
  
  Recurrent networks: Elman and Jordan networks, LSTM
  
  Clustering: density estimation; self-organizing maps
  
  Project: Software implementation of particular models and their simple applications.

PV027 Optimization

zk 2/0 2 kr., podzim

• doc. RNDr. Radka Svobodová, Ph.D.
• Prerequisities: Prerequisites: mathematical analysis MB001 Calculus II and linear algebra MB003 Linear Algebra and Geometry I.
• Goals: This is a basic course on methods of mathematical optimization and their practical use.
  Graduate will gain orientation in methods of mathematical optimization.
• Learning outcomes: Graduate will be able to select appropriate optimization method to solve a particular problem.
  Graduate will be able to explain principles of optimization methods.
• Syllabus: Unconstrained optimization: Nelder--Mead method, steepest descent, Newton methods, conjugate gradient, trust region methods. Least squares problem and analysis of experimental data.
  Linear programming, revised Simplex method, interior point methods. Applications of linear programming. Integer programming, branch and bound method. Dynamic programming.
  Nonlinear constrained optimization: penalty functions, quadratic programming, sequential quadratic programming method.
  Global optimization: simulated annealing, genetic algorithms, diffusion equation method.

PV028 Applied Information Systems

k 2/0 2 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Goals: The course deals with development of information systems.
• Learning outcomes: At the end of the course students should be able: -understand and explain principles and needs of information systems in medicine, business, manufacturing, and government - analyze the problem and describe a principle of solving it
• Syllabus: Synopsis Definitions of AIS
  Examples of some AIS (medicine, bussiness, industry, goverment)
  & Comparison of information systems - analogies and specifics.
  & Application of CASE tools.
  & Management methods for large-scale projects.
  & Design of large-scale information systems.
  & Sample design of an information system.

PV043 Enterprise Information Systems

k 2/0 2 kr., podzim

• RNDr. Pavel Hajn
• Prerequisities: PV063
• Goals: The aim of this course is to apprise the students of procedures of analysis, design, implementation, establishing and running of IS in companies. Basic terms: design, analysis, project and project exploitation. Program implementation, team of programmers. System establishing and system running.
• Learning outcomes: Student will be able to estimate the cost related with development, deployment, and maintanance of an information systems.
• Syllabus: The aim of this course is to apprise the students of procedures of analysis, design, implementation, establishing and running of IS in companies.
  Basic terms: design, analysis, project and project exploitation.
  Program implementation, team of programmers.
  System establishing and system running.
  The course includes the knowledge and experience of the managers and programmers of IS in the following companies: DOPLA PAP Sušice a.s. and OHLŽS Brno a.s.

PV045 Information System Management

zk 2/0 2 kr., podzim

• Mgr. Radek Foltýn - Ing. Leonard Walletzký, Ph.D.
• Goals: The course is about to present basic consequences of architecture of ERP systems. ERP system is analyzed not only from customer´s point of view (its functionality and utility) but also from the point of view of developer and software analytic.
• Learning outcomes: Student will understand to:
  - suggest and design the stucture of ERP implementation process
  - know the basic functionality of ERP system
  - describe the relations among basic modules of ERP system
  - know the basic possibilities of ERP customization
• Syllabus: Introduction, Information system, Basic model of IS life cycle, ERP system, iDempiere, Basic configuration and customization, Basic modules in the system, From quote to invoice, From requisition to invoice , Payments – cash and bank, Accounting, Reporting,

PV047 Topics in GIS I

z 0/2 2 kr., podzim

• RNDr. Milan Drášil, CSc. - RNDr. Rudolf Richter, CSc.
• Prerequisities: Relational databases. Basic techniques used in GIS.
• Goals: The course is focused to team work of students in analysis, design and GIS application development. Teams of students follow the steps of the structured and/or object methodics. In each step, the roles (analyst, administrator of data sources, design expert) are assigned to team members. The results of each step are demonstrated in public. Part I of this course is focused to analysis of GIS application. The course is extended to comment methodical principles.
• Learning outcomes: At the end of the course students should be able to: understand and explain metods of GIS projects; work with this information to realization of GIS project; create design of small GIS.
• Syllabus: In the first part, Design and Analysis of GIS projects I, the course contains the following phases.
  - Requirements collection, strategic plans of customer, environment of the company, geographic reflections, financial and time limits
  - Process and data analysis - conceptual level, decomposition of processes, entities and relations, diagrams (DFD-diagram, ER-diagram, UML diagrams)
  - Detailed analysis of the system, detailed entities and relations description including attributes, types and domains, functional analysis, cross reference of elementary functions and entities, life cycle of the instances of all entities
  Output of first part of the course is document containing detail analysis of system.

PV056 Machine Learning and Data Mining

zk 2/0 3 kr., jaro

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Prerequisities: A student needs to be familiar with basics of machine learning (e.g. IB031 Introduction to machine learning).
• Goals: At the end of the course students should be able to use machine learning and data mining methods. They will be able to built tools for mining in data that employ machine learning methods.
• Learning outcomes: A student will be able
  - to pre-process data for data mining;
  - to know advanced method of machine learning and data mining and to use them;
  - to write a technical report;
  - build and validate an advanced machine learning/data mining method.
• Syllabus: Introduction to the theory of knowledge discovery in databases. Survey of the most important methods, algorithms and systems. A project is as a part of the course.
  Knowledge discovery in databases. Data mining.
  Basic algorithms of machine learning.
  Preprocessing.
  Mining frequent patterns and association rules.
  Data visualization, visual analytics
  Text mining, mining in spatio-temporal dat, web mining.
  Data mining and life sciences.

PV057 Accouting and Managerial Economics

zk 2/0 2 kr., jaro

• RNDr. Pavel Hajn
• Prerequisities: PV063
• Goals: The goal of the course is to teach students the principles of accounting, chart of accounts, income statement, balance sheet, year-end processing, value added tax, reporting to tax authorities, Computerized accounting, database design.
• Learning outcomes: Student will have basic orientation in accounting principles for the purpose of usage, design and implementation of information systems.
• Syllabus: Basic information on accounting, chart of accounts, income statement, balance sheet, year-end processing, value added tax, reporting to tax authorities.
  Computerized accounting, database design.
  Accounting integration in the information system, relations to other modules.
  Cash flow, costs and revenues of costs centres and a company.
  Medium- and long-term company financial management strategy information system design.

PV062 File Structures

zk 2/0 2 kr., jaro

• doc. Ing. Jan Staudek, CSc.
• Goals: At the end of the course students should be able
  understand and explain data coding
  apply data compressing algorithms
  use file systems interfaces
  apply indexing and hashing to file structures
• Learning outcomes: At the end of the course students should be able
  understand and explain data coding
  apply data compressing algorithms
  use file systems interfaces
  apply indexing and hashing to file structures
• Syllabus: Information theory, data coding techniques
  Data Compression
  Secondary Memories
  File systems
  Sequential Files Organization
  Indexes, Index-Sequential File Organization, Inverted File Organization
  Hashing, hash index tables, Direct Access File Organization
  Trees, B+ tress, B trees

PV063 Database System Applications

zk 2/1 3 kr., jaro

• RNDr. Pavel Hajn
• Goals: The goal of the course is to teach students the principles of information systems and using databases for creation IS.
• Learning outcomes: Student will undestand the concepts of interaction of information systems and databases, and will be able to reason about such concepts as and design them.
• Syllabus: What is an information system and a DBS?
  Transactional and OLAP database.
  Tools for IS creation.
  Modern information systems.
  In-Memory Data Management - introduction

PV065 UNIX -- Programming and System Management I

zk 2/0 2 kr., podzim

• RNDr. Jan Kasprzak, Ph.D.
• Prerequisities: Prequisities: Students should go through the PV004 UNIX, should be able to write programs in C, and to have experiences with UNIX from the user's point of view (it is not recomended to attend this course for students who absloved the PV004 UNIX in last semester).
• Goals: The course introduces the principles of UNIX operationg system and its application interface (system calls, library functions). Students will learn about the UNIX kernel architecture, file system, processes, etc., both from the point of view of the kernel implementation and internals, and from the point of view of the UNIX application interface.
• Learning outcomes: After attending this coures, students will be able to:
  Understand the interaction beween programs in C and the system kernel.
  Use the POSIX.1 application interface to create programs in C.
  Use files, processes, and other tools, provided by the UNIX kernel to the applications.
  Have the basic understanding of the UNIX kernel, device management and memory management inside the kernel, and inner working of processes inside the kernel.
• Syllabus: UNIX development tools: compilers, debuggers, profilers and some other tools. Libraries, their types and function.
  C-language API standards.
  Program in the ANSI C: limits, start and end of program, arguments, environment variables, memory management, long jumps. Dynamic linking.
  Kernel: start of the system, architecture of the kernel, memory model of the kernel.
  Process: attributes of the process, states of the process, memory from the process' view, access rights of the process. Program on the disk.
  I/O operations: descriptor, operations with descriptors.
  File system organization: i-node and its attributes, directories and manipulation with directories, special files. Implementation of the FS: FAT, S5FS, FFS/UFS, Ext2FS. Modern file systems.
  Interprocess communication: pipes, signals, reliable signals.
  Advanced I/O: multiplexing using select() and poll(), file locking, scatter-gather I/O, memory-mapped I/O.

PV066 Typography I

k 1/1 2 kr., jaro

• MgA. Jana Malíková
• Prerequisities: PV123 && SOUHLAS
  Subject "Typography and Graphic Design" pressuposes a creativity as well as respecting the nature of the subject including a manual work depending on a set task.
• Goals: This course is an introduction to the basics of typography. Students create typical media such as advertisement or typographic poster. At the end of the course students will know the basic principles of typographic composition, will be able to elaborate designs for basic typographic media, will be able to design advertisement and will be able to design typographic poster.
• Learning outcomes: Student will learn how to compose picture and typographic elements, will be able to think about composition of a graphical design. Part of the output is a set of posters focusing on typography.
• Syllabus: Typographic composition.
  Typographic abstraction.
  Typographic illustration.
  Typographic poster.

PV067 Typography II

zk 1/1 2 kr., podzim

• MgA. Jana Malíková
• Prerequisities: PV066 && souhlas
  Subject "Typography" presupposes creativity as well as respecting the nature of the subject including a manual work depending on the set task. Prerequisite PV066
• Goals: This course provides theoretical and practical knowledge for book design. Students will create five designs book covers for any book series and one layout of a book. At the end of the course, students will know the basic principles of book design, will be able to elaborate designs for book covers and will be able to project a complete book. This course includes practical skills in Adobe InDesign and knowledge of typesetting and typographic rules.
• Learning outcomes: Student will be able to: - define typographic terminology; - create a book layout; - Orientation in typesetting; - to distinguish between good and bad typography; - practically apply a typographically correct typesetting; - orientated in Adobe InDesign; - reproduce print data; - to discuss Czech typographic rules; - present and defend book creation;
• Syllabus: Typographic sketch.
  Five book covers.
  Book layout.
  Book model in electronic and printed form.

PV070 Digital Libraries

zk 2/0 2 kr., podzim

• RNDr. Miroslav Bartošek, CSc.
• Prerequisities: ! FF:VIKBA25
  
• Goals: The aim is to introduce computer science students into the current state of practice of digital libraries.
• Learning outcomes: At the end of the course students should be able to understand principles and context of basic standards, technologies and principles used in design and implementation of digital libraries.
• Syllabus: Introduction to digital libraries (DLs): definitions, history, sources of information.
  Architecture of DLs: the Kahn-Wilensky framework; digital objects and repositories; social, legal and economic framework of DLs; hierarchical abstraction of intellectual creations.
  Global names and identifiers: traditional library identification systems and new digital identifiers; resolution of identifiers; persistency of identifiers; identifiers ISBN, ISSN, SICI, URL, URN, PURL, ISNI, ISTC, handles, DOI.
  Metadata: bibliographic library metadata and new "network" metadata schemas; MARC; Dublin Core; standards MODS and METS; application of XML and RDF.
  Interoperability: Z39.50 protocol; SRW/U; OAI; Open and context-sensitive linking, OpenURL.
  Global resource discovery: comparision of DLs and Internet search engines; federated searching and metasearching; semantic Web.
  Economic and legal context of DLs: business models; intellectual property rights; copyright; Czech copyright law; creative commons; open access.
  Long-term preserving of digital information: risks assessments; preserving strategies; OAIS reference model.
  Selected DL-projects and technologies presented by students in form of essayes and presentations.

PV072 Humanitarian Computer Applications

k 0/2 2 kr., podzim

• RNDr. Jaromír Plhák, Ph.D.
• Goals: Ethically motivated computer applications are the main goal of this seminar. The central topic is the computer support of the visually, hearing and mentally impaired people. The main objective is to introduce the field and present the possibilities that assistive technologies provide.
  At the end of the course students should be able to:
  - to understand use of assistive technologies by handicapped people,
  - to understand conventions used in accessible software development,
  - to understand how to overcome barriers to communication with handicapped people.
• Learning outcomes: After completing this course, student will be able to:
  - describe and summarize the use of assistive technologies by people with disabilities as well as the areas where assistive technologies are used;
  - apply the principles of making accessible software;
  - write a survey about one specific AT area;
  - present the results of their own work in front of the audience.
• Syllabus: 1) Introduction to the seminar. Discussion about the seminar content and students’ expectations. Project topics proposal.
  2) Presentation of specialist in the field of assistive technologies.
  3-12) Students' presentations.
  13) Students' presentations evaluation, feedback from students.

PV077 UNIX -- Programming and System Management II

zk 2/0 2 kr., jaro

• RNDr. Jan Kasprzak, Ph.D.
• Prerequisities: Only students who went through PV065 UNIX -- Programming and System Management I course, or those who have excellent knowledge about UNIX file system, kernel, and POSIX.1 API, should enroll to this course.
• Goals: The course gives the basic information about the UNIX system administration, the operation of the UNIX system in the networked environment, network applications programming using the BSD sockets API, information about some networking protocols (SMTP, HTTP, NFS etc), and their usage and administration on the UNIX-like systems.
• Learning outcomes: After attending this course, students will be able to:
  Understand the system of users and groups under UNIX.
  Understand the basic configuration of various subsystems under UNIX.
  Understand the architecture of the TCP/IP networks, and be able to program UNIX network applications, as well as configure the UNIX networking.
  Be able to configure selected UNIX network services.
• Syllabus: System of files and directories. Users and groups. Other system tables.
  Basic system programs: init and the start of the system, syslogd, update.
  Printer subsystem.
  Disk quotas.
  TCP/IP network basics: IP, ARP/RARP, ICMP, UDP and TCP layers; packet formats; principles of TCP/IP operation.
  Network programming (BSD sockets API): Socket, socket types; system calls for socket manipulation; connected and unconnected sockets; system tables and function for reading them; examples of applications.
  Low-level network administration: Giving an address to the interface; routing table; static and dynamic routing.
  TCP/IP over ethernet: ARP/RARP configuration; proxy ARP.
  Serial communication basics: Synchrohous and asynchronous communication; modems; point-to-point protocol (PPP); SLIP.
  DNS and address translation; Inet-daemon and the TCP-wrapper; services run from the inetd.
  Electronic mail: Principles of operation; simple mail transfer protocol (SMTP); sendmail.
  WWW: Hypertext transfer protocol (HTTP), http-daemon, national language problems.
  Network security and firewalls: Packet filtering; application gateways; network topology; virtual private networks; secure shell.
  X Window system.
  IPv6 basics.

PV078 Graphic Design I

k 1/1 2 kr., jaro

• MgA. Jana Malíková
• Prerequisities: PV123 && SOUHLAS
  Subject "Graphic Design" presupposes a creativity as well as respecting the nature of the subject including a manual work depending on the given task.
• Goals: This course helps students to develop the basic skills in the creation of graphic compositions and work with typography (recommended course PV066: Typography I). In the study process of this course students meet with the basics of pre-press. This course aims to introduce students to the main problems of graphic design: graphic stylization, abstraction, nonverbal communication, interpretation and presentation.
• Learning outcomes: Student will understand the basic terminology, will be able to work with professional software for vector grpahics, will be able to articulate her own drawing concepts and realize a given design. Student will be able to create a pictogram set on a given topic.
• Syllabus: Graphic poster.
  Pictogram and signage system.
  Illustrations.

PV079 Applied Cryptography

zk 1/1 3 kr., podzim

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
• Prerequisities: IV054 || now ( IV054 ) || PřF:M0170 || souhlas
  It is recommended to register this course after a cryptography course (M0170 or IV054), and it is also useful to have PV157 prior to this course.
• Goals: To teach the students to:
  understand intermediate-level issues of deploying cryptographic mechanisms;
  apply a crypto or security standard to fit the solution sought;
  judge pros and cons of crypto methods considered for deployment;
  independently design and test simple cryptographic solutions;
  evaluate common crypto protocols in terms of their security and efficiency.
• Learning outcomes: At the end of the course students will be able to:
  understand intermediate-level issues of deploying cryptographic mechanisms;
  apply a crypto or security standard to fit the solution sought;
  judge pros and cons of crypto methods considered for deployment;
  independently design and test simple cryptographic solutions;
  evaluate common crypto protocols in terms of their security and efficiency.
• Syllabus: This course explores the issues of applied cryptography issues, and topics cover: Relations of symmetric and asymmetric cryptography.
  Generation of random and pseudorandom sequences.
  Hash functions and their applications.
  Digital signatures, MAC. Non-repudiation.
  Cryptographic protocols, entity authentication.
  Public key infrastructure, certification.
  Patents and standards.
  Application of cryptography in selected systems - wireless sensor networks, smartcards, privacy enhancing technologies.

PV080 Information security and cryptography

zk 2/2 3 kr., podzim

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - RNDr. Marek Kumpošt, Ph.D.
• Prerequisities: This course aims at students in their second years of study, getting them exposed to the elementary aspects of IT (cyber) security and cryptography - fundamentals of algebra and programming are therefore expected.
• Goals: The aim is to teach the students to:
  explain the importance of information privacy and to illustrate negative impacts of its breach by examples;
  show advantages or disadvantages of basic IT security and privacy methods;
  judge impact of IT deployment on personal data and to judge ethical aspects of considered solutions;
  explain the importance of proper ways to security from risk analysis, through security policy up to the development and management of mechanisms - namely those based on cryptography;
  assess suitability of deploying selected tools for security and privacy support.
• Learning outcomes: At the end of the course students will be able to:
  explain the importance of information privacy and to illustrate negative impacts of its breach by examples;
  show advantages or disadvantages of basic IT security and privacy methods;
  judge impact of IT deployment on personal data and to judge ethical aspects of considered solutions;
  explain the importance of proper ways to security from risk analysis, through security policy up to the development and management of mechanisms, namely of cryptographic algorithms;
  assess suitability of deploying selected tools for security and privacy support.
• Syllabus: Concept of information privacy and relevant technical aspects, IT influence and relations.
  Protection of private data and legislation.
  Cryptographic functions and protocols.
  Digital identity, access management.
  Ethics, professional behavior and maintenance of information.
  Introduction to IT security.
  Network security.
  Secure programming.
  Usable security.
  Audit, revision of countermeasures, security operations.
  Security standards, evaluation criteria.

PV080 Information security and cryptography

zk 2/2 3 kr., jaro

• prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - RNDr. Marek Kumpošt, Ph.D.
• Prerequisities: This course aims at students in their second years of study, getting them exposed to the elementary aspects of IT (cyber) security and cryptography - fundamentals of algebra and programming are therefore expected.
• Goals: The aim is to teach the students to:
  explain the importance of information privacy and to illustrate negative impacts of its breach by examples;
  show advantages or disadvantages of basic IT security and privacy methods;
  judge impact of IT deployment on personal data and to judge ethical aspects of considered solutions;
  explain the importance of proper ways to security from risk analysis, through security policy up to the development and management of mechanisms - namely those based on cryptography;
  assess suitability of deploying selected tools for security and privacy support.
• Learning outcomes: At the end of the course students will be able to:
  explain the importance of information privacy and to illustrate negative impacts of its breach by examples;
  show advantages or disadvantages of basic IT security and privacy methods;
  judge impact of IT deployment on personal data and to judge ethical aspects of considered solutions;
  explain the importance of proper ways to security from risk analysis, through security policy up to the development and management of mechanisms, namely of cryptographic algorithms;
  assess suitability of deploying selected tools for security and privacy support.
• Syllabus: Concept of information privacy and relevant technical aspects, IT influence and relations.
  Protection of private data and legislation.
  Cryptographic functions and protocols.
  Digital identity, access management.
  Ethics, professional behavior and maintenance of information.
  Introduction to IT security.
  Network security.
  Secure programming.
  Usable security.
  Audit, revision of countermeasures, security operations.
  Security standards, evaluation criteria.

PV083 Graphic Design II

zk 1/1 2 kr., podzim

• MgA. Jana Malíková
• Prerequisities: PV078 && souhlas
  Subject "Graphic Design" presupposes creativity as well as respecting the nature of the subject including a manual work depending on the set task. Prerequisite PV078
• Goals: This course is a follow-up of the course Graphic Design I. It focuses on corporate identity and creating a graphic manual. At the end of the course students: - will know how to design a symbol, logotype, and their combination; - will be able to apply pictograms and logotype to various media; - will understand the principles of graphical manual design; - will gain the practical experiences with various graphics tools.
• Learning outcomes: A student will be: - orientated in a corporate design terminology; - know how to design a symbol or logotype or their combination; - be able to apply symbol or logotype to various media; – create an electronic version of design manual; – able to reproduce print data; - gain the practical experiences with various graphics tools in Adobe Illustrator, InDesign, and Photoshop CS6.
• Syllabus: Creating sign or logotype.
  Construction and codification of a sign or logotype.
  Graphics manual.
  Creation of stationery and advertising material.
  Presentation of sign or logotype.

PV084 Type Design I

k 1/1 2 kr., podzim

• Mgr. Lukáš Pevný
• Prerequisities: PV123 && SOUHLAS
  Precondition for this course is the artistic approach and the respect for the character of the subject, including the partial manual execution of the projects.
• Goals: The course introduces the foundations and basic skills of working with letters leading to the understanding of the construction of letter glyph, its history and classification.
• Learning outcomes: Student is familiar with the history of script and is able to draw and construct historical characteristics of typographic script, knows the basic classification of types and is able to create a character based on the classified group. Student knows the typographic terminology and is able to use it in appropriate manner.
• Syllabus: - Creating and typesetting of type-specimen book - Graphic desing of the free letter composition for the cover of the type-specimen book

PV085 Type Design II

zk 1/1 2 kr., jaro

• Mgr. Lukáš Pevný
• Prerequisities: PV084 && souhlas
  A precondition for this course is the artistic approach and the respect for the character of the subject, including the partial manual execution of the projects.
• Goals: The course introduces the foundations and basic skills of working with letters on which premises students will create authorial text or experimental letter set.
• Learning outcomes: A student is able to solve complex task - creation of the experimental concept of a set of characters. - is able to create the character set of a classic authorial alphabet with the consideration of its legibility, formal unity and other aesthetic criteria.
• Syllabus: - Creation of every letter of the alphabet presented in drawings - Execution of the authorial letter in graphics software - Application of the authorial letter set

PV090 UNIX -- Seminar of System Management

k 0/3 4 kr., podzim

• RNDr. Jan Kasprzak, Ph.D.
• Prerequisities: We expect the advanced knowledge of UNIX (Linux) on the user and programmer level and positive attitude towards UNIX. Before enrolling this course the students should go through PV065 UNIX -- Programming and System Management I and PV077 UNIX -- Programming and System Management II.
• Goals: The course provides practical introduction to the administration of UNIX systems and their services. Students will have an opportunity to install their own UNIX system, configure the kernel, networking (IPv4, IPv6), and several network services (e-mail, WWW server, LDAP, Kerberos, etc).
• Learning outcomes: After attending this coures students will be able to: Install and configure the UNIX system.
  Customize the kernel configuration for the particular application.
  Configure and maintain network services, running on UNIX systems.
• Syllabus: Operating system installation, basic networking configuration (IPv4, IPv6), firewall configuration.
  Configuring kernel and optimizing it for a particular HW.
  Virtualization, virtual machine installation.
  DNS: name server configuration.
  E-mail: SMTP, POP3, IMAP, spam detection methods.
  WWW, HTTP servers, SSL, proxy cache.
  Network monitoring (SNMP, MRTG, Nagios, Zabbix, Smokeping, arpwatch/ndpmon).
  Databases of users, LDAP, modular authentication with PAM.
  Kerberos; time synchronization over network.
  Network traffic classification.

PV094 PC Hardware

zk 3/0 3 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D.
• Prerequisities: Knowledge of computer systems architectures, that is adequate to the course PB150 Computer-Systems Architectures or PB151 Computer Systems.
• Goals: The course PC Hardware gives detailed information on technical realization of modern computer systems. The students get acquainted with particular components of current computers, their properties, connection, operational principle, and with possibilities of their usage.
• Learning outcomes: At the end of this course, students should:
  know concepts dealing with hardware;
  know operational principles of particular components;
  be able of qualified hardware purchase;
  be able to identify bugs in a computer;
  be able to make some repairs in a computer (exchange of a certain module);
  be able to plug in a new module into the computer (including its correct setting).
• Syllabus: Architecture of PC and its peripheries.
  Mainboard.
  Microprocessors Intel.
  Internal memories and their technological realization. Cache memories.
  Bus, width, speed, comparison, compatibility.
  Magnetic data recording. Hysteresis of ferro-magnetic materials.
  External memories. Magnetoresistive heads.
  Interfaces between controllers and hard disk units.
  Graphic cards. Port A.G.P.
  I/O card. Serial and parallel data transfer.
  Soundcards, record and synthesis of a sound. MIDI. Speaker systems.
  Monitors. Principle of a color CRT. LCD displays and their operational principle. Plasma displays.
  PCMCIA standards and USB bus. Standard IEEE 1394.
  Memory media, cassettes, magnetic discs.
  Magneto-optical discs, CD-ROM, CD-R, CD-RW, DVD, and Blu-ray discs.
  Printers.
  Review of other devices.

PV097 Visual creativity informatics

zk 2/1 3 kr., jaro

• Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: Knowledge of computer graphics algorithms (in the scope of PB009 Principles of Computer Graphics course). Basic programming skills. Creative thinking and artistic abilities are highly appreciated.
• Goals: The course is aimed at the visual creativity informatics issues. Students gain theoretical knowledge as well as practical skills.
  At the end of this course, students should be able to:
  understand principles of creative informatics art-works creation;
  interpret given visual art-work;
  design new art-works using available software;
  design and implement aesthetically productive algorithms.
• Learning outcomes: After finishing this course, a student should be able to:
  - analyze and describe existing computer-aided artworks
  - use existing software tool to create computer-aided art artefacts
  - design and implement software tools for computer-aided art
• Syllabus: Computer-aided visual art concepts.
  Brief history of computer-aided art.
  Aesthetically productive algorithms.
  Ornaments.
  Mosaic.
  Knots.
  Fractal graphics.
  Bioart.
  Communication graphics and visual perception.
  Non-photorealistic rendering.
  Procedural generation of 3D model, fabrication options.

PV109 History of IT and Trends in Computing

k 2/0 2 kr., podzim

• doc. RNDr. Eva Hladká, Ph.D. - prof. RNDr. Luděk Matyska, CSc.
• Prerequisities: Any student of Masaryk University may enlist to this course provided that he or she has not passed it (under any code).
• Goals: The course is intended for students who seek information on the development of computing aids and information technology since the ancient times and on expected further development of the branch.
• Learning outcomes: At the end of this course student will know individual phases of the historical evolution of computer technology at large and specifically in the Czechoslovakia.
  She will be able to name the most influential persons and their contribution to the evolution of computer technology.
  He will be able to describe primary evolution trends and influencing principles.
  Using the historical know-how she will be able to make simple predictions of future evolution in major areas of IT.
• Syllabus: Pre-history of computing (from abacus to Babbage).
  First computers.
  Why to be interested in the history of IT. Formerly used terms. 1st to 5th computer generations. Hardware and software approach to the notion of the generation. Families of computers. Digital, analog and hybrid computers.
  Historical computer components and peripherals. Former view at main computer parts. Types of store. External storage devices. I/O devices.
  Personal recollections at IT used in our country. First computers in former Czechoslovakia. How programming the LGP-30 computer looked like. Research Institute of Mathematical Machines and its main achievements. EC and SM computer families.
  From machine code to programming languages. Languages that principally affected further language development (Algol, Fortran, Cobol, Basic, PL/I, APL, Lisp, Simula, Pascal, C).
  Operating systems. Computers without an OS. Toward an OS. Components of modern OS. Examples of OS.
  Trends in H/W and S/W. CISC/RISC, integration, dependencies between H/W, S/W and OS. Networks and Internet. Diversion from procedural languages?
  Compures and society. Computer: a tool, a partner, or a menace?

PV110 Základy filmové řeči

k 2/2 4 kr., podzim

• Mgr. BcA. Robert Král, Ph.D. - doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: Prerequisites for enrollment and successful completion are only enthusiasm for cinematography, ability to work effectively in a team, communicate, solve problems, manage crisis situations and relative time flexibility. The student does not need to have knowledge of the film industry. Knowing the basics of creative writing and electronic publishing PB029 Electronic Document Preparation is a plus.
• Goals: The aim of PV110 and PV113 Production of Audiovisual Artefacts is to enable students to express their own via movie language. This is gradually learned by writing and filing his own subject, literary and technical scenario, preparing a technical scenario for his film production in the follow-up spring semester in the course PV113 Production of Audiovisual Artefacts, and by discussing principles and gaining practical skills from areas of editing, engaging, camera, scene lighting, scene sound, and postproduction.
• Learning outcomes: At the end of the course, the student will be able to:
  - use the knowledge of the basics of screenwriting, dramaturgy, direction, production in writing his own theme, literary and technical scenario; - prepare a technical scenario and production of a short movie; - use the acquired knowledge of editing, cutting, engaging, camera, scene lighting, scene sound and postproduction in the movie production; - create a film crew with fixed roles from the group of students; - produce his own short audiovisual work.
• Syllabus: Theme. Literary model for movie or multimedia project. Choice of model or intrigue. Basics of scriptwriting. Movie script: analysis of conflict, the setting of key points in a script, plausibility of figures, dynamics of the storytelling, characters and their progress. The substance of dramaturgy, collective readings, processes towards final script and technical and production plan. Main rules of production and postproduction. Editing. Practical goal is an adaptation of literary model into the movie script. Students have to write or adapt a story into a script, taking in mind existing technical backing of the course in LEMMA laboratory. During the realization of this goal, students will be taught the right ways of doing a good script and all the phases of literary preparation (model, story, script) all the topics around. Scripts written and defended in the course will be used for movie/multimedia production in the Spring term. Practical exercises will be done in the LEMMA laboratory using DLSR and other rich sets of audio and video instruments.

PV112 Computer Graphics API

zk 2/2 3 kr., jaro

• RNDr. Jan Byška, Ph.D.
• Prerequisities: Practical knowledge of C/C++ or Java required.
• Goals: The goal of this subject is to provide students with overview of computer graphics interfaces. Students also gain a practical knowledge of standard OpenGL Application Programming Interface. When completing this course, students will be able to implement a broad spectrum of computer graphics applications.
• Learning outcomes: After passing this course, students will be able to: - understand the existing implementations of GPU algorithms - design and implement simple GPU algorithms - apply the knowledge about GPU implementation of basic methods of computer graphics to our tasks in CG
• Syllabus: Aplication interfaces for Computer Graphics.
  Basic principles of rendering using powerful graphics accelerators, OpenGL Shading Language.
  Rendering pipeline.
  Structure and functions of graphics API.
  Data types and graphic primitives.
  Coordinate systems, transformations.
  Vertex buffer objects, vertex array objects, lighting, materials.
  Alpha blending, fog, bitmaps.
  Texturing, multitexturing.
  Per-fragment operations, other effects.

PV113 Production of Audiovisual Artefacts

k 2/0 5 kr., jaro

• doc. RNDr. Petr Sojka, Ph.D. - Mgr. BcA. Robert Král, Ph.D.
• Prerequisities: SOUHLAS
  (APPROVAL)
  Asking for approval is possible in these cases:
  
  A) the student has his/her technical scenario that s/he created within course PV110 Základy filmové řeči previous semester approved OR did not complete PV110 in the previous semester, but has his/her own technical scenario that s/he wants to have approved and then shoot it OR participate in the process of making,
  B) the student wants to participate in organizing the festival,
  C) the student wants to pass the course in the form of a colloquium, and therefore wants a combination of A) and B).
  
  A prerequisite is a passion for creative activity, specifically for multimedia communication via audiovisual works, or is interested in participating in organization of the festival. For more information about approval, detailed requirements or rules visit page https://is.muni.cz/auth/el/1433/jaro2020/PV113/index.qwarp.
• Goals: At the end of this course, students are able to: identify and work with the basic concepts and roles in the production process of multimedia work, work in teams to produce film and animation work and present it at the Film Festival FI MU at the end of the semester. In the case of the festival organization, the students improve their communication, teamwork and generally the organization or compliance with deadlines.
• Learning outcomes: Student will be able to:
  - Film theme, literary and technical scenario,
  - Produce a short-distance team in the team,
  - Know the roles and communicate in groups representing the film crew.
• Syllabus: Production and preparation of the film festival.
  Filming and realization of their own shots.
  Excursion to the TV studio.
  Film Festival.

PV115 Laboratory of Knowledge Discovery

z 0/0 2 kr., podzim

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Prerequisities: souhlas
  
• Goals: At the end of the course students should be able to create systems for knowledge discovery in data.
• Learning outcomes: A student will be able
  - to understand research papers from machine learning and data mining;
  - of critical reading of such papers;
  - to build and validate a machine learning or data mining method.
• Syllabus: Students participate on research projects in various areas of knowledge discovery and data mining:
  Project proposal
  Consultation during the term
  Presentation of results, a final report It is appropriate for beginners as well as for those who look for help in solving more complex tasks of machine learning and data mining.

PV115 Laboratory of Knowledge Discovery

z 0/0 2 kr., jaro

• doc. RNDr. Lubomír Popelínský, Ph.D.
• Prerequisities: souhlas
  Prerequisite for enrollment in the subject is 1) being familiar with basic machine learning 2) being fluent in English 2) approval of the application by the teacher Students being interested in longer than one semester collaboration will be prefered.
• Goals: At the end of the course students should be able to create machine learning systems for data analysis.
• Learning outcomes: A student will be able
  - to understand research papers from machine learning and data mining;
  - of critical reading of such papers;
  - to build and validate a machine learning or data mining method.
• Syllabus: Students participate on research projects in various areas of machine learning and data science:
  Project proposal
  Consultation during the term
  Presentation of results, a final report

PV119 Elements of Law

zk 2/0 2 kr., podzim

• RNDr. JUDr. Vladimír Šmíd, CSc.
• Goals: The basic goal of the lecture is to explain the priciples of law as a instrument of society control and survay of individual branches of law oriented on obtaining of basic practical orientation connecting with informatics.
• Learning outcomes: Student will get basic practical orientation in legal aspects related to informatics.
• Syllabus: Priciples of law as a instrument of society control.
  Elemantary concepts of law theory.
  Legal authority and incidence.
  Survay of individual branches of law oriented on obtaining of basic practical orientation connecting with Informatics: -- civil law -- commercial law -- labour law -- international private and commercial law -- land law -- constitutional law -- administrative law -- penal law -- environmental law -- international public law.

PV120 Information Law

zk 2/0 2 kr., jaro

• RNDr. JUDr. Vladimír Šmíd, CSc.
• Prerequisities: PV119 is recomended but not necessary.
• Goals: The basic goal of the lecture is to explain the legal aspects of some parts of informatics, especially personal protection, commercial secret, intellectual property, personal data protection, classified fact and free access to informations.
• Learning outcomes: Students will understand legal aspects of IT production and will be able to recommend basic steps leading towards protection of intelectual property.
• Syllabus: Informational liberty and legal protection of personal data -- constitutional principles, Charter of Fundamental Rights and Freedoms.
  Foreign examples and international context -- law in abroad, recommendations, agreements and directives of international and supranational organizations.
  Private law protection of informations and information systems -- personal protection, commercial secret, labour discipline etc.
  Intellectual property law -- author law, industrial property.
  Personal Data Protection -- the Act, its application, Office for Personal Data Protection.
  Public law protection of informations and information systems -- penal law protection.
  Classified Fact Act.
  Free Access to Informations Act.

PV123 Introduction to Visual Communication

k 2/0 2 kr., podzim

• MgA. Helena Lukášová, ArtD. - MgA. Jana Malíková - Mgr. Lukáš Pevný
• Prerequisities: Prerequisite for: Script I, Typography I, Graphic Design I, Photography I ( prerequisite for Photography I is this course or Historical Changes of Photography)
• Goals: The objective of the course is to present principles of the visual communication and to stress the importance in the contemporary information society. The information has new potention through the digital media. The course introduces topics throught the compilation of lectures discussing topics such as perception and interpretation of the reality, semiotics, relationship of visual perception and read information, new media, principles of graphic design and its history, principles of font creating and typography, introduction to moving pictures, digital fabrication.
• Learning outcomes: Students will understand the topic of visual communication in relation to information technologies. Students will understand the inter-relationship between written information and depiction of a information in visual form, development of representation of perspective, writting, animation, graphic design. They will also learn about semiotics theories.
• Syllabus: Introduction - What is visual communication, representation, mimesis, eidetic reduction, problem of depiction of abstract concept.
  Interpretation of the space - fropm reality to illusion. Creation of the meaning - semiotic theories - dualistic, triadic, connotation, dennotation, mythology.
  Digital media. Idea as the final product and the new possibilities of its processing.
  Photography and its message. The theory of communication as the universal foundation of the photography.
  Type in context of its construction, creation and classification.
  Work with type, Work with the fonts with the emphasis on the formal and conceptual point of view.
  General problematics of the graphic design. What is graphic design, presentation of the examples of works of czech and worldwide famous graphic designers. Basic rules of graphic design.
  Information design. Relation of the function and the form.
  Legal protection of author's work and related legal issues.
  How to be the graphioc designer and not to loose the mind. Broader view on the position of graphic designer, realion to a client. An idea and communication as the basis of succesful result.
  Digital fabrication as a third industrial revolution

PV131 Digital Image Processing

zk 2/2 3 kr., jaro

• prof. RNDr. Michal Kozubek, Ph.D.
• Prerequisities: Required knowledge: English, foundations of mathematics, linear algebra, calculus and basics of image processing at the level of PB130 course.
• Goals: This course aims to broaden the knowledge of the basics of digital image processing gained in the PB130 course. The students will gain an overview of the available techniques and possibilities of this field. They will learn image transforms, segmentation algorithms and problems of object classification. They will be able to perform the basic techniques and apply them in practice. The lecture serves as the base for all those who want to attend to the topic in more detail.
• Learning outcomes: The student will be able to:
  - formulate basic principles of digital image processing;
  - describe mutual relations between the analysis in spatial and frequency domain;
  - realize basic workflows at least in MATLAB;
  - suggest and apply suitable workflows for a given problem of image analysis;
• Syllabus: Acquisition of 2D and 3D image data, the process of signal digitization.
  Properties of digital images.
  Continuous convolution, PSF, OTF.
  Fourier transform and Nyquist sampling theorem.
  Image processing in the frequency domain.
  Non-linear filters.
  Multi-scale analysis, introduction to wavelet transform.
  Hough transform and Radon transform.
  Image segmentation.
  Image and object classification.
  Deep learning and convolutional neural networks in image analysis.

PV136 DB Systems Seminar

k 0/1 1 kr., jaro

• RNDr. Miroslav Křipač, Ph.D.
• Prerequisities: PB154 Database Systems recommended.
• Goals: This course provides practical expirence with database application development and database systems production. Main objectives can be summarized as follows: - To learn database systems fundamentals. - To apply new database management trends to practices.
• Learning outcomes: understand database system architecture; maintain and tune database systems
• Syllabus: Database Systems Architecture Overview
  Oracle DBMS Architecture
  Efficient Database Applications
  Transactions
  Performance Tuning
  Database Systems Hardware
  Database Clusters
  Databases and Clouds

PV156 Digital Photography

k 1/1 2 kr., podzim

• RNDr. Vít Kovalčík, Ph.D.
• Goals: The course aims to familiarize the student with all the main practical aspects of taking and processing photographs.
• Learning outcomes: At the end of the semester, the student will be able to understand principles of the photographic hardware, including parameters and internal operation of cameras and lenses. They will be also able to perceive the usual compositional rules and manage the basic processing of the photographs on the computer.
• Syllabus: Different types of photographic cameras, non-standard cameras, digital sensor types (CCD, CMOS, SuperCCD, Foveon), sensor strengths and weaknesses, crop factor and full frame, other parts of photographic devices. Strengths and weaknesses of digital photography.
  Lens types, characteristics, and usage, non-standard lenses. Lens characterization and build. Optical and build defects. Other photographic accessories.
  Basics of photographs taking. Compositional rules, setting the exposure, explaining the relations between the aperture, exposure time and sensitivity.
  Format types (JPEG, TIFF, RAW), basic and advanced adjustment in photo editing, work with layers, software for photo editing. Removing defects made by sensors or lens. Further possibilities for digital photography (collage, photo-graphics...).

PV160 Laboratory of Human-Computer Interaction

z 0/0 2 kr., podzim

• Mgr. Jiří Chmelík, Ph.D. - doc. RNDr. Barbora Kozlíková, Ph.D.
• Prerequisities: souhlas
  Applicants should: - be able to work in teams,
  - have interest in long-term projects (several semesters),
  - have good practical knowledge of programming using C++, C#, or Java;
• Goals: Students work in Human-Computer Interaction Laboratory and participate in research of various fields of computer graphics, virtual reality, brain-computer interfaces, haptic-based interaction etc.
• Learning outcomes: At the end of the course students:
  - will be familiar with modern VR equipment installed in the HCI Laboratory;
  - will practise usage of graphics and haptics libraries and toolkits;
  - will learn to design and assemble computer graphics applications;
  - will be able to develop and test new human-computer interaction methods;
  - will improve their abilities to work in small teams on non-trivial theoretical and practical problems.
• Syllabus: In the Laboratory of Human-Computer Interaction, students solve individually or in teams; various projects focused on new forms of multimodal interaction based on virtual reality techniques. The work concentrates on algorithmic and system problems of computer graphics in general, interfaces, position detection, haptic feedback, and interconnection of solutions into functional systems.

PV160 Human-Computer Interaction Laboratory

z 0/0 2 kr., jaro

• Mgr. Jiří Chmelík, Ph.D. - doc. RNDr. Barbora Kozlíková, Ph.D. - RNDr. Jan Byška, Ph.D.
• Prerequisities: souhlas
  Applicants should: - be able to work in teams,
  - have interest in long-term projects (several semesters),
  - have good practical knowledge of programming using C++, C#, or Java; Windows or UNIX/Linux,
  - have basic knowledge of English (written and spoken).
• Goals: Students work in Human-Computer Interaction Laboratory and participate in research of various fields of computer graphics, virtual reality, brain-computer interfaces, haptic-based interaction etc.
• Learning outcomes: At the end of the course students:
  - will be familiar with modern VR equipment installed in the HCI Laboratory;
  - will practise usage of graphics and haptics libraries and toolkits;
  - will learn to design and assemble computer graphics applications;
  - will be able to develop and test new human-computer interaction methods;
  - will improve their abilities to work in small teams on non-trivial theoretical and practical problems.
• Syllabus: In the Laboratory of Human-Computer Interaction, students solve individually or in teams; various projects focused on new forms of multimodal interaction based on virtual reality techniques. The work concentrates on algorithmic and system problems of computer graphics in general, interfaces, position detection, haptic feedback, and interconnection of solutions into functional systems.

PV162 Image Processing Project

k 0/2 2 kr., podzim

• doc. RNDr. Petr Matula, Ph.D.
• Prerequisities: SOUHLAS
  Knowledge at the level of course PV131 or at least PB130 is required
• Goals: The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
• Learning outcomes: At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
• Syllabus: Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  Programming: implementation and testing of a given algorithm (in a chosen programming language)
  Creative: finding a suitable solution to a given problem
  Study: testing and comparison of several algorithms/implementations on a given data

PV162 Image Processing Project

k 0/2 2 kr., jaro

• doc. RNDr. Petr Matula, Ph.D.
• Prerequisities: souhlas
  Knowledge at the level of course PV131 or at least PB130 is required
• Goals: The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
• Learning outcomes: At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
• Syllabus: Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  Programming: implementation and testing of a given algorithm (in a chosen programming language)
  Creative: finding a suitable solution to a given problem
  Study: testing and comparison of several algorithms/implementations on a given data

PV165 Process Management

zk 1/1 2 kr., jaro

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: The basic knowledge of software engineering principles and techniques.
• Goals: Main objectives can be summarized as follows:
  to understand the process management and workflow systems;
  to learn to plan, execute and monitor business processes;
  to learn to estimate, control and optimize the process time, cost and quality.
• Learning outcomes: Students will understand the basic concepts and principles of business process management. At the end of the course, the student will be able to design a simple process structure that he / she can develop and optimize in terms of time and cost.
• Syllabus: History, Process Management, Business Processes.
  Workflow, Workflow System, Workflow Reference Model.
  Workflow Enactment Service (WES).
  Workflow Application Programming Interface & Interchange (WAPI).
  Process Definition Tools (PDT), Workflow Process Model.
  User and Application Interfaces and Communication.
  Communication with other Workflow Systems.
  Administration and Monitoring.
  Process Efficiency Determination.
  Process Simulation.
  Process Optimisation, CPI, BPR.
  BPMN (Business Process Modelling Notation).
  BPEL (Business Process Execution Language).
  Using UML for Process Modeling.
  CASE Tools of Process Modeling.
  Commercial Workflow Products.
  Workflow Standards.
  Workflow Application Development, Project Management.

PV167 Seminar on Design and Architecture Patterns

z 0/2 2 kr., podzim

• RNDr. Radek Ošlejšek, Ph.D.
• Prerequisities: PA103 || now ( PA103 )
  Practical seminar supporting the theoretical lecture PA103 Object-oriented Methods for Design of Information Systems. We expect knowledge of object-oriented paradigm, core knowledge of software engineering, knowledge of UML models.
• Goals: Understanding of key principles and usability of software patterns;
  Deeper understanding of properties of selected patters;
  Application of analysis and design patterns on particular complex system;
  Decomposition of a system based on its software architecture;
  Introduction to the measurement and optimization of software quality;
• Learning outcomes: At the end of the course, a student should be able to:
  - decompose software applications according to the principles of software architectures and tactics;
  - describe software decomposition by means of UML models;
  - describe properties of selected analysis and design patterns;
  - apply analysis and design patterns during the decomposition of object-oriented and component systems;
  - discuss properties of software patterns - assess impact of the application of patterns on software quality;
• Syllabus: Introduction to the Visual Paradigm CASE system, project assignment.
  Use-case driven requirements.
  Analysis patterns.
  Application of selected analysis patterns.
  Design patterns.
  Application of selected design patterns.
  Presentation and discussion of approaches, project defense.
  Models of software architecture, component decomposition.
  Software quality, qualitative attributes. Analysis of selected qualitative attributes (reliability, performance) of component models.

PV168 Seminar in Java programming

z 2/2 3 kr., podzim

• doc. RNDr. Tomáš Pitner, Ph.D. - Ing. Petr Adámek - RNDr. Martin Kuba, Ph.D.
• Prerequisities: Java programming knowledge covered by the course PB162.
• Goals: The goal of this course is to extend the basic knowledge of Java and master its practical application in concrete projects. The student will be able to appropriately decompose simple programming tasks and write robust code including automated tests. The student will get acquainted with basics of GUI development, multithreaded applications, and fundamental APIs. Further, the student will be able to develop simple database (JDBC) and web applications. After passing the course, the student is expected to be capable of designing and developing simple applications in Java.
• Learning outcomes: Student will be able to:
  - do object design in Java;
  - use and write unit tests in JUnit;
  - access relational databases in Java via JDBC;
  - write flawless multithreaded applications;
  - save configurations, write internationalized and localized applications, use log records;
  - write very simple Java web applications over basic API (servlet, JSP);
  - describe the principles of applications with a graphical user interface;
  - write simple applications with GUI in Java;
  - optimize and debug application performance.
• Syllabus: Object-oriented design in Java
  Testing, Unit Testing, JUnit
  Databases in Java, JDBC
  Multithreaded Applications
  Storing Configuration, Internationalization and Localization, Logging
  Introduction into Web applications development
  GUI Applications
  Optimization and Performance Tuning

PV169 Communication Systems Basics

zk 2/0 2 kr., podzim

• doc. Ing. Jan Staudek, CSc.
• Goals: At the end of the course students understand the basic principles of data transmission
• Learning outcomes: Understanding the basic principles of data transmission
• Syllabus: Signals
  Digital transmission
  Analog transmission
  Transfer media
  Multiplexing
  Switching
  Error Control
  Data Link Control
  Medium Access Control

PV170 Design of Digital Systems

zk 2/0 3 kr., podzim

• prof. Ing. Václav Přenosil, CSc. - RNDr. Zdeněk Matěj, Ph.D.
• Prerequisities: Course PV170 is an introductory subject of study. It is advisable to complete the course PB170 in parallel. In course PB170 you will gain practical experience and skills of working with digital circuits, with digital circuit design systems and digital circuit modeling and simulation.
• Goals: The main aim of this course is to understand and master basic theoretical knowledge and practical virtuosity necessary for description and design of the digital systems. The lessons specialises in particular into the following topics:
  - fundamentals of the logical algebra and logical function.
  - design of the simple combination circuits.
  - design of the elemental sequential circuits.
• Learning outcomes: The student understands the fundaments of logic algebra, combination circuit design, sequential circuit design.
• Syllabus: Theory of the encoding and data representation
  Logic algebra and optimization of logical terms.
  Implementation arithmetic and logical operations into digital systems.
  Realization and principles of digital circuits.
  Optimization of digital circuits structure and operation.
  Fundamental logic circuits and digital computer modules
  The methodology of combinational and sequential circuits design.
  Basic operational units of digital systems

PV171 Digital Systems Diagnostics

zk 2/0 2 kr., podzim

• prof. Ing. Václav Přenosil, CSc. - RNDr. Zdeněk Matěj, Ph.D.
• Prerequisities: Courses PV170 - Design of Digital Computers and PV172 - Architecture of the digital systems is an advisable source of necessary knowledge for the current course.
• Goals: The main aim of this course is to understand and master fundamental theoretical knowledge of the technical system reliability theory. The lessons are specialized in particular into the following topics:
  - theory of the reliability of the technical system,
  - theoretical and operative diagnostic of the digital systems,
  - most important principles, models, and applications of the redundancy.
• Learning outcomes: A student is able to understand and use:
  - theory of the reliability of the digital systems,
  - theoretical and operative diagnostic of the digital systems,
  - most important principles, models, and applications of the redundancy.
• Syllabus: Theory of the reliability
  Hardware and software reliability of the digital systems
  Definition of the reliability, classification of the failures and numerical parameters of the reliability
  Grounding notations of technical diagnostics, failures model of the technical systems
  Assembly methods of the detection and location tests
  Checking of the failure-free activity, relaxation after failure, reconfiguration, depletion of the operation
  Fault-tolerant systems and redundancy
  Fundamental of the technical systems predicting diagnostics
  Hardware and software functionality checking tools of the digital system
  Hardware and software diagnostics tools of the digital systems
  Microprocessors systems testing and ROMBIOS

PV172 Architecture of Digital Systems

zk 2/0 2 kr., jaro

• prof. Ing. Václav Přenosil, CSc. - RNDr. Zdeněk Matěj, Ph.D.
• Prerequisities: Course PV170 - Design of Digital Systems is advisable source of necessary knowledges for current course.
• Goals: Main aim of this course is understand and master theoretical knowledge necessary for design high-performance digital systems.
• Learning outcomes: Students will be capable of:
  application of the fundamental design components;
  understanding principle of the modular systems design methodology;
  design and implement connection of external devices.
• Syllabus: Controllers and Sequencers
  Structure of the digital systems
  Addressing of the memory
  Instruction set of the typical microprocessor
  Memories and Cache memories
  Structure of the typical processor and its interrupt system.
  Direct memory access
  External busses
  Auxiliary circuits
  A/D converters
  D/A converters
  Input/output circuits
  Diagnostics system
  Checking circuits

PV173 Natural Language Processing Seminar

k 0/2 2 kr., podzim

• doc. RNDr. Aleš Horák, Ph.D. - doc. Mgr. Pavel Rychlý, Ph.D. - prof. PhDr. Karel Pala, CSc.
• Prerequisities: Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
• Goals: The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
• Learning outcomes: After the seminar, the students will:
  - gain insight into recent works in the field of computer natural language processing (NLP);
  - be able to discuss NLP issues and solutions;
  - understand an evaluation of NLP problems on the data sets used;
  - design and present a custom solution for a selected NLP problem.
• Syllabus: The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.

PV173 Natural Language Processing Seminar

k 0/2 2 kr., jaro

• doc. RNDr. Aleš Horák, Ph.D. - doc. Mgr. Pavel Rychlý, Ph.D. - prof. PhDr. Karel Pala, CSc.
• Prerequisities: Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed.
• Goals: The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
• Learning outcomes: After the seminar, the students will:
  - gain insight into recent works in the field of computer natural language processing (NLP);
  - be able to discuss NLP issues and solutions;
  - understand an evaluation of NLP problems on the data sets used;
  - design and present a custom solution for a selected NLP problem.
• Syllabus: The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.

PV174 Laboratory of Electronic and Multimedia Applications

k 0/0 2 kr., podzim

• doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: souhlas
  Willingness to work on LEMMA Lab projects in the following areas:
  - research in the areas of search and representation of knowledge, digital typography, machine learning, ... (spring and autumn); - use of video technology for e-learning and the preparation of educational video materials (spring and autumn); - Support and mentoring of the course (autumn) and (spring) with the production of the traditional Film Festival of the Faculty of Informatics (Spring).
• Goals: The aim of the course is to teach students how to work independently on audiovisual projects of the laboratory (film festival, materials for e-learning, documentary projects and their mentoring), or participation in laboratory research.
• Learning outcomes: Student will be able to:
  - participate in multimedia production and cooperate on the organizational and creative aspects of the creation of short films or
  - research work and communication in a team.
  Students also improve their soft skills.
• Syllabus: Audiovisual section LEMMA:
  Available camera technology and its capabilities for low cost production. Preparation of documentation and recommendations for shooting procedures.
  Available sound technology and its use possibilities. Document processing and recommendations for sound recording workflows.
  Available photo technology and its use possibilities. Document processing and workflow recommendations scanning, documentary photography.
  Available sw for mass word processing. Document processing and workflow recommendations for working with large databases of texts (DVD 10 @ FI type).
  Research section LEMMA:
  Fundamentals and principles of research work in mir.fi.muni.cz, gait.fi.muni.cz or lemma.fi.muni.cz

PV174 Laboratory of Electronic and Multimedia Applications

k 0/0 2 kr., jaro

• doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: souhlas
  Willingness to work on LEMMA Lab projects in the following areas:
  - research in the areas of search and representation of knowledge, digital typography, machine learning, ... (spring and autumn); - use of video technology for e-learning and the preparation of educational video materials (spring and autumn); - Support and mentoring of the course (autumn) and (spring) with the production of the traditional Film Festival of the Faculty of Informatics (Spring).
• Goals: The aim of the course is to teach students how to work independently on audiovisual projects of the laboratory (film festival, materials for e-learning, documentary projects and their mentoring), or participation in laboratory research.
• Learning outcomes: Student will be able to:
  - participate in multimedia production and cooperate on the organizational and creative aspects of the creation of short films or
  - research work and communication in a team.
  Students also improve their soft skills.
• Syllabus: Audiovisual section LEMMA:
  Available camera technology and its capabilities for low cost production. Preparation of documentation and recommendations for shooting procedures.
  Available sound technology and its use possibilities. Document processing and recommendations for sound recording workflows.
  Available photo technology and its use possibilities. Document processing and workflow recommendations scanning, documentary photography.
  Available sw for mass word processing. Document processing and workflow recommendations for working with large databases of texts (DVD 10 @ FI type).
  Research section LEMMA:
  Fundamentals and principles of research work in mir.fi.muni.cz, gait.fi.muni.cz or lemma.fi.muni.cz

PV175 MS Windows Systems Management I

k 1/2 3 kr., podzim

• Mgr. Libor Dušek
• Prerequisities: Knowledge of operating systems fundamentals (at least comparable to PB152 Operating Systems course). User experience with Windows XP or later.
• Goals: Main objective of this course is to provide students with solid knowledge needed for implementing and supporting client MS Windows operating systems. Course can be used as a preparation for Microsoft "Exam 70-698"
• Learning outcomes: Student is able to administrate desktop workstations with MS Windows.
• Syllabus: Installation of Windows 10
  Basic System Configuration
  User & Group Accounts
  Configuring Network Connectivity
  Active Directory Fundamentals
  NT File System, File Sharing, Local & Network Access Permissions
  Hardware Devices & Drivers
  Disk & Data Management
  Security Audit
  Backing Up and Restoring Data
  Supporting Remote Users
  Troubleshooting the Boot Process
  Windows Registry
  Encrypting File System
  Scripting basics

PV176 MS Windows Systems Management II

zk 0/2 3 kr., jaro

• Mgr. Libor Dušek - RNDr. Šimon Suchomel, Ph.D. - Mgr. Martin Čuchran - Ing. David Leška - Mgr. Ondrej Šebela
• Prerequisities: PV175 || souhlas
  Knowledge of operating systems fundamentals at least comparable to PB152 Operating Systems course. User experience with Windows 7 or later. It is recommended to complete the PV175 MS Windows Systems Management I course.
• Goals: The course provides students with solid knowledge needed for designing, implementing and managing the Active Directory (AD) network by means of MS Windows Server operating system. This knowledge includes introduction to logical and physical AD structure, account policy implementation, domain controllers replication, security management, AD backup or remote software installation via group policies. The lessons are realised on Windows Server 2012 R2.
• Learning outcomes: Student will be able to perform basic administration of Winodws-based systems.
• Syllabus: Active Directory domain for complex management of Windows environment
  Networking in Windows Environment
  Name Resolution - DNS, NetBIOS
  Basic AD operations - management of users, groups and organizational units
  Group Policy - computer settings, software installation
  Operations Masters
  Physical and logical topology
  Server and desktop security

PV177 Laboratory of Advanced Network Technologies

z 0/2 2 kr., podzim

• doc. RNDr. Eva Hladká, Ph.D. - prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - RNDr. Tomáš Rebok, Ph.D.
• Prerequisities: souhlas
  Specialization "Big Data Analytics in Practice" - none
  Specialization "Computer Networks" - completed PB156, preferably also PA159
• Goals: Familiarization with the area and practical team project aimed at adopting the principles in one of the areas, which the course is specialized on in the particular semester.
  In autumn 2019, the course is specialized in the following areas:
  1. Big Data analytics in practice -- the aim of this course's specialization is to introduce students to methods and tools for analyzing large data volumes (so-called Big Data), which will then be examined in the form of practical projects presented at the end of the semester.
  2. Advanced Computer Networks -- the aim of this specialization is to introduce students to the area of computer networks and related technologies, research methodology, own research and presentation of results. The work is separated into two semesters, begin in the fall semester with lower network levels (physical infrastructure, construction of computer halls, basic protocols from level two = STP, 802.1Q,...), in spring semester work follows with protocols on L3, mostly routing protocols (OSPF, BGP). Sprig semester follows the fall.
• Learning outcomes: Getting new knowledge in the chosen area of interest and working on a practically-oriented team project.
• Syllabus: Team project in one of the areas, which the course is specialized on in the particular semester: Big Data analytics, computer networks, grids or multimedia. Students can choose or are assigned a practical project (team-based, i.e. an assignment will be solved by a group of students). When solving the project, students will master the advanced understanding of a subject, acquire basic research methodology, will optionally perform the research and will present achieved results. The work progress will be evaluated on regular weekly or two-weekly seminars, where students will receive the necessary feedback on their undertakings.
  The last seminar will be devoted to the overall evaluation and students will receive credits.

PV177 Laboratory of Advanced Network Technologies

z 0/2 2 kr., jaro

• doc. RNDr. Eva Hladká, Ph.D. - Ing. Jana Hozzová, Ph.D. - Mgr. Aleš Křenek, Ph.D. - Mgr. Martin Macák - prof. RNDr. Václav Matyáš, M.Sc., Ph.D. - RNDr. Tomáš Rebok, Ph.D. - RNDr. Vít Rusňák, Ph.D.
• Prerequisities: souhlas
  PV177/DataScience (Big Data Analytics in Practice) -- none
  PV177/Experiments (Modelling and Evaluation of Experiments) -- basic mathematics (MB101-MB103, resp. MB202-203) and programming (IB111, IB113)
  PV177/ComputerNetworks (Computer Networks) -- completed PB156, preferably also PA159
• Goals: Familiarization with the area and practical (team) project aimed at adopting the principles in one of the areas, which the course is specialized on in the particular semester.
  In current semester, the course is specialized in the following areas:
  1. PV177/DataScience (Big Data analytics in practice) -- the aim of this course's specialization is to introduce students to methods and tools for analyzing large data volumes (so-called Big Data), which will then be examined in the form of practical projects presented at the end of the semester.
  2. PV177/Experiments (Modelling and Evalution of Experiments) -- the aim of this course's specialization is to introduce students to methods and tools for modelling and quantitative and qualitative evaluation of experiments, which will then be examined in the form of three practical projects throughout the semester.
  3. PV177/ComputerNetworks (Advanced Computer Networks) -- the aim of this specialization is to introduce students to the area of computer networks and related technologies, research methodology, own research and presentation of results. The work is separated into two semesters, begin in the fall semester with lower network levels (physical infrastructure, construction of computer halls, basic protocols from level two = STP, 802.1Q,...), in spring semester work follows with protocols on L3, mostly routing protocols (OSPF, BGP). Sprig semester follows the fall.
• Learning outcomes: Getting new knowledge in the chosen area of interest and working on a practically-oriented (team) project.
• Syllabus: 1. PV177/DataScience (Data Analytics in Practice):
  Team project in one of the areas, which the course is specialized on in the particular semester: Big Data analytics, computer networks, grids or multimedia. Students can choose or are assigned a practical project (team-based, i.e. an assignment will be solved by a group of students). When solving the project, students will master the advanced understanding of a subject, acquire basic research methodology, will optionally perform the research and will present achieved results. The work progress will be evaluated on regular weekly or two-weekly seminars, where students will receive the necessary feedback on their undertakings.
  The last seminar will be devoted to the overall evaluation and students will receive credits.
  
  2. PV177/Experiments (Modelling and Evaluation of Experiments):
  Seminar will be done in four blocks, in 2., 5., 8. and 11. week of the semester, each time for 6 hours, dates will be discussed with students and determined after the beginning of the semester.
  1) Quantitative evaluation: what is hypothesis and how to formulate it, what can happen (false negative, true negative, false positive, true positive), how to control the false positive error rate, how to ensure high statistical power, what means statistically significant result, p-value and its interpretation, what is pre-registration and how to use it.
  2) Modelling: introduction to mathematical and computational models, parametrization of models towrads experimental data, least squares method; goodnes of fit evaluation, application of quantitative evaluation (presented in the first block), under- and overfitting; advanced techniques (mixed models etc.).
  3) Qualitative evaluation and user testing: types of qualitative experiments (questionnaires, interviews and focus groups, …), formative and summative testing, standardized questionnaires, goals and phases of the analysis of qualitative data.
  Each part includes a project. Students are encouraged to bring their own (evaluation in their thesis or its part). If they do not have their own data, a project will be assigned.
  
  3. PV177/ComputerNetworks (Computer Networks):
  Team project specialized in an area of computer networks, grids or multimedia. Students can choose or are assigned a practical project (team-based, i.e. an assignment will be solved by a group of students). When solving the project, students will master the advanced understanding of a subject, acquire basic research methodology, will optionally perform the research and will present achieved results. The work progress will be evaluated on regular weekly or two-weekly seminars, where students will receive the necessary feedback on their undertakings.
  The last seminar will be devoted to the overall evaluation and students will receive credits.

PV178 Introduction to Development in C#/.NET

k 1/2 3 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D. - doc. Ing. RNDr. Barbora Bühnová, Ph.D. - Mgr. Martin Macák
• Prerequisities: PB161 || PB162
  
• Goals: The aim of the course Introduction to Development in C#/.NET is to familiarize students with the C# programming language, the Visual Studio development environment and the main techniques accompanying the development of C#/.NET applications.
• Learning outcomes: At the end of this course the student should:
  - know basic tasks and techniques accompanying the development process of C#/.NET applications;
  - be familiar with Visual Studio environment;
  - know the essential features and programming constructs of C# programming language;
  - be able to write high-quality C# code.
• Syllabus: The C# programming language and MS .NET Framework.
  Programme structure in C#.
  Common type system (value types, reference types).
  Class type and its members.
  Namespaces.
  Parameter-passing, overloading of methods.
  Encapsulation, inheritance, polymorphism (virtual methods).
  Abstract methods (abstract classes).
  Interfaces.
  Exceptions.
  Enumeration types.
  Array, string and struct types.
  Generics.
  Collections.
  Iterators.
  Delegates (anonymous methods, lambda expressions), events.
  File input/output (streams).
  LINQ (LINQ to Objects).
  Paralel and asynchronous programming.

PV179 System Development in C#/.NET

k 2/2 3 kr., podzim

• doc. Ing. RNDr. Barbora Bühnová, Ph.D. - Mgr. Martin Macák
• Prerequisities: Basic knowledge of the C# language (best on the level of PV178), basic knowledge of HTML, and knowledge at the level of PB154 and PB007.
• Goals: The course will extend the knowledge gained in PV178 Introduction to Development in C#/.NET through practical work on a specific project. The students will learn to create a non-trivial web application in ASP.NET Core, create REST interface, work with the ORM framework, and understand the practical usage of enterprise design patterns and other good practices. Some of the chosen lectures also introduce to students the development of various kinds of applications with the focus on the techniques and technologies supporting this task.
• Learning outcomes: At the end of the course the students will know typical applications of the .NET framework and be able to:
  - describe some of the essential technologies used in the .NET environment;
  - understand and apply the principles of the multi-tier architecture;
  - write applications using persistence and ORM;
  - apply the enterprise design patterns;
  - use good practices (for example Dependency Injection, mapping, common design patterns);
  - design the application independently from the chosen ORM framework and choose the right persistent technology for the given project;
  - test the individual parts of the application in isolation;
  - create the non-trivial web application on ASP.NET Core platform;
  - integrate the authentication and secure the application against the most common attacks;
  - create REST interface for the web application.
• Syllabus: Data layer (Entity Framework Core, querying)
  Business logic layer (structure and related design patterns)
  Presentation layer (ASP.NET Core MVC, ASP.NET Core Web API, autentization)

PV180 Social informatics project

k 0/2 2 kr., jaro

• RNDr. Jaromír Plhák, Ph.D.
• Prerequisities: PV262 || souhlas
  It is expected that students propose their own topics for their projects.
  Basic knowledge in the field of social informatics is expected (SIN01). The basic level of knowledge of methodology of conducting an empirical study is required as well (PV262).
  Previous undertaking of PV072 is welcomed, especially in case you will work on project in the field of assistive technologies. Previous undertaking of PV182 is welcomed, especially in case you will work on project in the field of human-computer interaction.
• Goals: The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of social informatics and practical checking of this knowledge by working on the project. Students are encouraged to implement an application in arbitrary programming language, conduct a qualitative or quantitative survey, conduct a simulation experiment, or develop a user interface prototype
  At the end of the course students should be able to analyze chosen topic in the field of social informatics and develop individual project.
• Learning outcomes: After completing this course, student will be able to analyze chosen topic in the field of social informatics and develop individual project.
• Syllabus: 1) Introduction to the seminar. Discussion about the seminar content and students’ expectations.
  2) Short presentation of students’ topics and chosen technologies. Discussion about the objectives of each project.
  3) Proposal of the schedule.
  4-7) Individual work on projects.
  8) Presentation of practical output.
  9-12) Individual work on projects.
  13) Project defense.

PV181 Laboratory of security and applied cryptography

k 0/2 2 kr., podzim

• Mgr. Marek Sýs, Ph.D.
• Prerequisities: Registration to PV181 requires: 1) long-term interest in IT security; 2) programming skills (ideally C and Java) under Unix/Linux or Win32; 3) fluent English.
• Goals: The aim of this subject is to understand implementation details of cryptographic algorithms and protocols and to be able to apply the gained knowledge in practice. At the end of the course students should be able to design and implement cryptographic applications independently.
• Learning outcomes: To teach the students to:
  select appropriate cryptographic functions;
  understand basic-level issues of implementating cryptographic applications;
  apply the gained knowledge in practice;
  judge pros and cons of crypto functions ;
  independently design and implement simple cryptographic applications in various enviroments;
  evaluate crypto applications in terms of their security and efficiency.
• Syllabus: Principles of cryptography and cryptographic standards (symmetric cryptography, random number generation, hash functions, asymmetric cryptography, certificates, certification authority, PKI). Using cryptographic libraries in cryptoaplications (OpenSSL, Cryptlib, Microsoft Crypto API, Java). Digital Signatures (CMS/PKCS#7 structure, S/MIME, Czech legislation). Formats of commmon cryptographic files (keys, certificates, ASN.1). Biometric systems (fingerprint, face).

PV182 Human Computer Interaction

zk 1/1 2 kr., jaro

• RNDr. Vít Rusňák, Ph.D.
• Goals: The course deals with basics of human-computer interaction. It focuses on psychological and physiological aspects of interface design, graphical user interface design and its usability assessment.
• Learning outcomes: After finishing the course students
  - will be able to evaluate existing screen designs;
  - will practise in developing human-computer interfaces with respect to a usability;
  - will be able to asses the usability of SW products;
  - will understand the usability issues in general;
  - will gain practical knowledge of designing process based on in-depth understanding of high and low-level models of human-computer interaction.
• Syllabus: Introduction to human-computer interaction. Task-centred system design.
  High level models of human-computer behaviour.
  User-centred design and prototyping.
  Evaluating interfaces with users.
  Evaluation - controlled experiments.
  Design of everyday things.
  Representations, visual variables, metaphors and direct manipulation.
  Evaluation based on cognitive models.
  Graphical screen design
  Physical user interfaces
  Heuristic evaluation of interfaces.

PV183 Computer Networks Technology

zk 2/0 2 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Prerequisities: ! PB157
  
• Goals: The main goal of the course Technology of Computer Networks is to provide students with information about technology and services that are used in modern computer networks. The students obtain information about particular network architectures, principles of local network administration, set of TCP/IP protocols, routing of information, and about the Internet.
• Learning outcomes: At the end of this course, students should know:
  transmission media and media access methods characteristics;
  various network architectures characteristics;
  possibilities of LAN design;
  fundamentals of wireless communication technologies;
  the OSI model;
  fundamentals of IPv4, ARP, TCP, UDP, and IPv6 protocols operation.
• Syllabus: Computer networks. Basic concepts, different sorts.
  Network topologies and their properties.
  Transfer media (thin and thick coax-cable, twisted-pair, fibre optic).
  Media access methods (deterministic and stochastic).
  Network architectures (Token-Ring, Ethernet, Fast Ethernet, Gigabit Ethernet, 10G Ethernet, FDDI, ATM, ...) and principles of their operation.
  Wireless communication technologies.
  Digital signal hierarchy. SONET/SDH. ISDN. DSL technology.
  Virtual networks (VLAN).
  The OSI Model.
  Protocols IPv4, ARP, TCP, and UDP. Routing in TCP/IP networks. IPv6 protocol.
  The Internet.

PV187 Seminar of digital image processing

z 0/0 2 kr., podzim

• prof. RNDr. Michal Kozubek, Ph.D. - doc. RNDr. Petr Matula, Ph.D. - doc. RNDr. Pavel Matula, Ph.D. - doc. RNDr. David Svoboda, Ph.D. - RNDr. Martin Maška, Ph.D.
• Prerequisities: souhlas
  Knowledge at the level of the course PV131 Digital Image Processing and PB130 Introduction to Digital Image Processing is required as well as practical experience with digital image processing (e.g., gained in course PV162 Image Processing Project).
• Goals: The student will gain a more profound knowledge about a chosen area of image processing solved in the Centre for Biomedical Image Analysis at FI MU and will study literature on a selected practical topic followed by a presentation in English. This will strengthen the student's capability of understanding real-world problems in the given field, finding suitable solutions and participating in scientific team discussions.
• Learning outcomes: The student will be able to:
  describe and share own image analysis solutions with colleagues;
  prepare an oral presentation about specific image analysis workflow;
  analyze strengths and weaknesses of image analysis workflows presented by others;
  suggest suitable modifications to image analysis workflows presented by others;
• Syllabus: This course is a seminar (presentations followed by team discussions) focused on methods of acquisition and processing of digital images of cells from optical microscopes, especially in connection with biomedical research held in the Centre for Biomedical Image Analysis at FI MU.

PV187 Seminar of Digital Image Processing

z 0/0 2 kr., jaro

• doc. RNDr. Petr Matula, Ph.D. - doc. RNDr. Pavel Matula, Ph.D. - prof. RNDr. Michal Kozubek, Ph.D. - RNDr. Martin Maška, Ph.D.
• Prerequisities: souhlas
  Knowledge at the level of the course PV131 Digital Image Processing and PB130 Introduction to Digital Image Processing is required as well as practical experience with digital image processing (e.g., gained in course PV162 Image Processing Project).
• Goals: The student will gain a more profound knowledge about a chosen area of image processing solved in the Centre for Biomedical Image Analysis at FI MU and will study literature on a selected practical topic followed by a presentation in English. This will strengthen the student's capability of understanding real-world problems in the given field, finding suitable solutions and participating in scientific team discussions.
• Learning outcomes: The student will be able to:
  describe and share own image analysis solutions with colleagues;
  prepare an oral presentation about specific image analysis workflow;
  analyze strengths and weaknesses of image analysis workflows presented by others;
  suggest suitable modifications to image analysis workflows presented by others;
• Syllabus: This course is a seminar (presentations followed by team discussions) focused on methods of acquisition and processing of digital images of cells from optical microscopes, especially in connection with biomedical research held in the Centre for Biomedical Image Analysis at FI MU.

PV188 Principles of Multimedia Processing and Transport

zk 2/0 2 kr., podzim

• doc. RNDr. Eva Hladká, Ph.D. - RNDr. Miloš Liška, Ph.D. - Ing. Pavel Šiler
• Goals: Taking this lecture, a student gets an overview in the area of multimedia processing and transfer through computer networks. Basic principles of audio and image (including video) coding and processing are presented, as well as basic methods of multimedia transmissions over using computer networks. The lecture also includes foundations of audio and video acquisition including the principles of acquisition devices.
• Learning outcomes: A graduate will be able to understand and explain principles of audio and video coding.
  A graduate will be also able to design a system for capture and transmission of multimedia data through a computer network.
  A graduate will be also able to select appropriate coding formats for multimedia, taking into account the requested quality and properties of the computer network.
• Syllabus: Audio acquisition, microphones
  Audio mixing, interconnection of components
  Video acquisition, cameras, lenses
  Camera operations
  Digital recording
  Sampling and quantization principles
  Audio and its perception
  Special audio coding, audio compression mechanisms (MPEG-I Layer 3, MPEG-4 Part-3, FLAC etc.)
  Image, video and its perception
  Fourier transformation, DCT, compression
  Compression mechanisms (MPEG family, Theora, Snow, Dirac), codecs, multimedia containers
  Multimedia transmissions, distribution mechanisms, unicast vs. multicast
  Audio and video conferences, streaming

PV189 Mathematics for Computer Graphics

zk 2/0 2 kr., podzim

• doc. RNDr. Pavel Matula, Ph.D.
• Prerequisities: Completion of MB151 and MB152 is the precondition.
• Goals: This lecture aims to enhance the mathematical foundations acquired through the previous studies. We focus on practical utilization of mathematics in the computer graphics area. The students gain an insight into the practical mathematics necessary for implementation of many computer graphics algorithms.
• Learning outcomes: After finishing the course the student will be able to: understand the common mathematics being used for solving computer graphics tasks; solve the typical tasks
• Syllabus: Revision of linear algebra. Vectors, matrices, linear transformations.
  Afinne geometry, homogeneous coordinates.
  Eigen values, eigen vectors and their geometric meaning.
  Principal component analysis.
  Interactions of basic objects in 3D (lines, planes, spheres).
  Rotation and quaternions.
  Sampling vs. interpolation of digital signal.
  Interpolation of rotation (LERP, SLERP, SQUAD, etc.).
  Minimization (linear and nonlinear regression).
  Geometrical properties of curves and surfaces (length, tangents, curvature, etc.).

PV191 Project from Designing Digital Systems

k 0/3 3 kr., jaro

• RNDr. Zdeněk Matěj, Ph.D. - RNDr. Martin Veškrna
• Goals: The course is suitable for students who are processing final theses. One is aimed at practical solutions to the particular problems of digital systems development. The aim is to gain practical experience and skills in the implementation and management of research and development activities related to the analysis, design, and implementation of specialized circuits, digital systems.
• Learning outcomes: At the end of the course, students will be able to:
  independent work in the design and implementation of the digital system
  
• Syllabus: IrDA port design, market analysis
  Data transmission using IrDA
  Current RF technology data transmission, market analysis
  Design of security device using RF data communication
  Freescale digital barometer data processing with barometric pressure display
  Touch graphical display control application
  Position and altitude display using GPS module
  MEMSIC accelerometer data filtration - inclinometer
  Hitachi Compass module control, azimuth measurement
  Humidity and temperature module data processing – display application
  Distance measurement using ultrasonic rangefinder module with object counter using reflexive IR module

PV197 GPU Programming

zk 1/1 2 kr., podzim

• RNDr. Jiří Filipovič, Ph.D.
• Prerequisities: IB109
  C programming basics, familiarity with CPU architecture and parallelization of algorithms.
• Goals: The goal of this course is to explain how to use GP GPU for general computation.
• Learning outcomes: After the end of the course students should: describe the architecture, programming model and optimization for GPUs; explain GPU implementation of several broadly used algorithms; create GPUs implementation of given computational tasks; judge the suitability of given computational problem for GPU acceleration.
• Syllabus: Introduction: motivation for GPU programming, GPU architecture, overview of parallelism model, basics of CUDA, first demonstration code
  GPU hardware and parallelism: detailed hardware description, synchronization, calculation on GPU -- rate of instruction processing, arithmetic precision, example of different approaches to matrix multiplication -- naive versus block-based
  Performance of GPUs: memory access optimization, instructions performance, an example of matrix transposition
  CUDA, tools and libraries: detailed description of CUDA API, compilation using nvcc, debugging, profiling, basic libraries, project assignment
  Optimization: general rules for algorithm design for GPU, revision of matrix multiplication, parallel reduction
  Parallelism in general: problem decomposition, dependence analysis, design analysis, parallel patterns
  Metrics of efficiency for GPU: parallel GPU and CPU usage, metrics for performance prediction of GPU code, demonstration using graphics algorithms, principles of performance measurement
  OpenCL: introduction to OpenCL, differences comparing to CUDA, exploiting OpenCL for hardware not accessible from CUDA
  Case studies 1: Calculation of force field of molecule, automatic optimization of memory-bound functions
  Case studies 2: Acceleration of image and video compression
  Case studies 3: LTL model checking acceleration
  Discussion of a project, presentation of best-achieved results, presentation of 3 best solutions by authors, final discussion

PV198 Onechip Controllers

k 2/0 3 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D.
• Goals: The main aim of this course is to understand and master theoretical knowledge and practical virtuosity necessary for description and for application of the microcontroller and microcomputer.
• Learning outcomes: At the end of the course, students will be able to:
  design single-chip microcomputer applications;
  to work with the C language in a single-chip microcomputer environment;
  program single-chip microcomputer applications;
  to work with peripherals of microcomputers (PWM, timer, ADC...).
• Syllabus: Programming of the microcontrollers:
  structure of the programming language
  control structures (Boolean expressions, conditions, cycles)
  bit operations and bit array
  terminal input/output
  control of memories
  pointers
  onedimension and multidimensional array
  structures, unions, enumeration types
  
  Program control of the peripheral units:
  serial ports
  LED, bargraph, switches, buttons, shift registers
  text and graphical displays
  interrupt systems
  counters and timers, PWM
  A/D and D/A converters
  control of the RAM, ROM and FLASH memories
  
  Practical advices:
  diagnostics, debugging
  safe programming
  projects administration

PV200 Introduction to hardware description languages

k 0/2 3 kr., podzim

• RNDr. Zdeněk Matěj, Ph.D.
• Goals: Within this course the students will obtain deeper knowledge on the field of programmable structures (e.g. FPGAs) and get familiar with advanced methods of hardware design using hardware description languages. Verilog HDL is used to demonstrate most of the principles.
• Learning outcomes: Graduates of this course will be able to:
  understand the FPGA principle;
  understand the programming languages VHDL and Verilog;
  design advanced systems using HDL languages;
  program application for FPGA.
• Syllabus: Programmable structures fundamentals.
  Verilog HDL – concepts, basic syntax, abstraction levels, design hierarchy.
  Designing in Verilog – combinational primitives, sequential circuits, state machine design.
  FPGA devices – capabilities, limitations, programming. Advanced features in Verilog, best practice.
  Prefabricated components – IP cores, Megafunctions.
  Interfaces & Peripherals – RS232, LCD, keyboard.
  Introduction to VHDL.
  Softcore computing – introduction to soft-core processor system.
  Practical tasks in Quartus II suite.

PV202 Service Systems Laboratory

k 0/0 2 kr., podzim

• Ing. Leonard Walletzký, Ph.D. - doc. Mouzhi Ge, Ph.D.
• Prerequisities: PB114 && souhlas
  Preconditions for this course are: (1) capability of autonomous work; (2) English; (3) wish to work as a member of a team;
• Goals: Objective to provide overall picture & insight on Cloud computing emerging area. Cloud computing is model that is becoming more and more important not only among biggest companies in the world, but practically everywhere in our daily life. Nowadays companies are already able to demonstrate that this new model is capable of creating real business benefits, new markets and opportunities. Course covers various aspects of cloud computing - e.g. virtualization, what the cloud computing is about, architecture, security in cloud computing, transition to cloud environment, business aspects & risks of this new phenomen and many others. During course labs students are expected to build their own virtualized cloud technology on their PCs or create application within PaaS environment (provided by RedHat or IBM).
• Learning outcomes: Upon completion students understand the principles of cloud computing and are able to design structure of a cloud computing application.
• Syllabus: Students are expected to select some of following labs (A or B or C):
  A) RED HAT - Integration of virtualized or hybrid cloud technology (oVirt or Red Hat OpenStack). Simple all-in-one setup would suffice. In such case it is possible to use laptop as hypervisor, within virtual machine it's possible to set up management platform. Final goal of such project is presentation of simple web application running inside a Virtual Machine managed by this infrastructure. Under this assignment the application is not expected to be overly complex. Expected time donation for this variants is 8 hours (pure time spent on task). Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.
  B) RED HAT - Delivery of application running on top of Red Hat OpenShift. This assignment is targeted for students who prefer web development over the integration of projects. Red Hat OpenShift provides basic free account which is enough for integrating large enterprise application with database resources (https://www.openshift.com/). End goal of OpenShift assignment is to have working OpenShift account running an instance of web site. Under this assignment students are expected to deliver rich interface web application in selected language (any of the ones OpenShift provides). Expected time donation for this variant is 8 hours (pure time spent on task). Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.
  C) IBM - includes 2 smaller exercises for PaaS and SaaS i.) PaaS - explore IBM PaaS (BlueMix - https://ace.ng.bluemix.net/) environment and deliver basic web application within this environment. Lab is expected to be concluded with presentation / demo of created application. ii.) SaaS - goal is to use IBM SaaS (BlueWorks). Student uses mentioned SaaS to demonstrate process flow showing steps, activities, roles /... that should be taken in account when cloud suitability for commercial client is being considered (imagine yourself to be in the position of consultant for commercial client). Student can demonstrate also process according own selection as alternative (but this case should be approved in advance and related to Cloud Computing). Lab is to be concluded with presentation (presenting process, and strong / week points of SaaS). This assignment is intended for students who prefers basic web development and would like to focus on business aspect of cloud computing within commercial environment (SaaS part of labs). Expected time donation for this variant (C.i + C.ii together) is 6 hours. Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.

PV202 Service Systems Laboratory

k 0/0 2 kr., jaro

• Ing. Leonard Walletzký, Ph.D.
• Prerequisities: Preconditions for this course are: (1) capability of autonomous work; (2) English; (3) wish to work as a member of a team;
• Goals: Objective to provide overall picture & insight on Cloud computing emerging area. Cloud computing is model that is becoming more and more important not only among biggest companies in the world, but practically everywhere in our daily life. Nowadays companies are already able to demonstrate that this new model is capable of creating real business benefits, new markets and opportunities. Course covers various aspects of cloud computing - e.g. virtualization, what the cloud computing is about, architecture, security in cloud computing, transition to cloud environment, business aspects & risks of this new phenomen and many others. During course labs students are expected to build their own virtualized cloud technology on their PCs or create application within PaaS environment (provided by RedHat or IBM).
• Learning outcomes: Upon completion students understand the principles of cloud computing and are able to design structure of a cloud computing application.
• Syllabus: Students are expected to select some of following labs (A or B or C):
  A) RED HAT - Integration of virtualized or hybrid cloud technology (oVirt or Red Hat OpenStack). Simple all-in-one setup would suffice. In such case it is possible to use laptop as hypervisor, within virtual machine it's possible to set up management platform. Final goal of such project is presentation of simple web application running inside a Virtual Machine managed by this infrastructure. Under this assignment the application is not expected to be overly complex. Expected time donation for this variants is 8 hours (pure time spent on task). Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.
  B) RED HAT - Delivery of application running on top of Red Hat OpenShift. This assignment is targeted for students who prefer web development over the integration of projects. Red Hat OpenShift provides basic free account which is enough for integrating large enterprise application with database resources (https://www.openshift.com/). End goal of OpenShift assignment is to have working OpenShift account running an instance of web site. Under this assignment students are expected to deliver rich interface web application in selected language (any of the ones OpenShift provides). Expected time donation for this variant is 8 hours (pure time spent on task). Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.
  C) IBM - includes 2 smaller exercises for PaaS and SaaS i.) PaaS - explore IBM PaaS (BlueMix - https://ace.ng.bluemix.net/) environment and deliver basic web application within this environment. Lab is expected to be concluded with presentation / demo of created application. ii.) SaaS - goal is to use IBM SaaS (BlueWorks). Student uses mentioned SaaS to demonstrate process flow showing steps, activities, roles /... that should be taken in account when cloud suitability for commercial client is being considered (imagine yourself to be in the position of consultant for commercial client). Student can demonstrate also process according own selection as alternative (but this case should be approved in advance and related to Cloud Computing). Lab is to be concluded with presentation (presenting process, and strong / week points of SaaS). This assignment is intended for students who prefers basic web development and would like to focus on business aspect of cloud computing within commercial environment (SaaS part of labs). Expected time donation for this variant (C.i + C.ii together) is 6 hours. Creativity of the solution is taken into account and will serve as one of the main decision points for final grade.

PV203 IT Services Management

zk 2/0 2 kr., jaro

• doc. Mouzhi Ge, Ph.D. - Ing. Vladimír Vágner
• Goals: This subject shows the emergence of service science, a new multidisciplinary area of study, to address the challenge of becoming more systematic about innovating in services. The subject points out solutions and proccesses mainly used in area of IT services.
• Learning outcomes: At the end of the course students should be able:
  to understand the paradigm shift from goods economy to service economy;
  to undestand outsourcing and data centers services;
  to formulate a Service Level Agreement;
  to understand the SaaS - Software as a Service approach.
• Syllabus: Service science
  IS/IT outsourcing
  Delivery center model
  Customer Support Center
  Server System Operations & Desktop Client Support
  Practical exercise
  Network Services Delivery
  Information Technology Infrastructure Library
  Outsourcing Infrastructure Services, Customer Support Services
  Further development of IS/IT outsourcing services

PV204 Security Technologies

zk 2/2 5 kr., jaro

• doc. RNDr. Petr Švenda, Ph.D. - Ing. Milan Brož, Ph.D. - Mgr. Vít Bukač, Ph.D. - RNDr. Václav Lorenc - Mgr. Milan Patnaik
• Prerequisities: Registration to PV204 requires: 1) long-term interest in IT security; 2) programming skills (ideally C and Java) under Unix/Linux or Windows; 3) fluent English.
• Goals: The aim of this subject is to understand the deeper aspects of selected security and applied cryptographic topics. The topics cover cryptographic hardware security, including side-channel attacks, secure authentication, and authorization protocols, trusted boot, analysis of malware and rootkits (both black-box and gray-box), reverse engineering of binary applications, techniques used in Bitcoin cryptocurrency, micro-architectural attacks like Meltdown and Spectre and file/disk encryption. Students should be able to apply the gained knowledge in practice based on experience gained from the laboratory, homework assignments, and extensive project work.
• Learning outcomes: After course completion, the student will be able to:
  - explain the security advantages of hardware security element to a typical desktop operating system;
  - analyze the implementation of a cryptographic algorithm for a presence of the timing side-channel;
  - describe and use good practices for password handling, including password alternatives and their advantages;
  - explain principles of key establishment protocols and building blocks of modern secure messaging systems;
  - explain principles and used technologies of trusted computing;
  - describe the technology behind disk encryption and used encryption modes;
  - perform basic analysis of infected computer image;
  - implement security-related application utilizing cryptographic smartcard with JavaCard platform and transfer data via a secure channel;
  - understand the root cause of micro-architectural attacks against modern CPUs
  - explain security building blocks of cryptocurrencies like Bitcoin
• Syllabus: Side-channel attacks (timing, power and fault analysis)
  Basics of smart cards (PC/SC, APDU, basic applet – JavaCard & .net card & MULTOS), secure programs on JavaCard platform
  Secure authentication and authorization (common protocols like FIDO U2F and Signal, secure implementation, attacks)
  Hardware Security Modules (HSM), PKCS#11 API, cryptographic hardware in cloud deployment
  Trusted boot (TPM, trusted boot process, remote attestation)
  Micro-architectural attacks against modern CPU (Meltdown, Spectre attacks principle, fixes, exploitability)
  Black-box analysis of malware (infection vectors, analysis of the environment, network analysis)
  Grey-box analysis of malware (analysis of memory dumps, tools)
  Reverse engineering of binary applications (decompiler, disassembler, native-code debugging, binary patching)
  File and disk encryption (Common architectures, used cryptographic modes, typical attacks)
  Bitcoin cryptocurrency (P2P Bitcoin network, transactions, mining, second-layer networks like Lighting Network, use of hardware wallets, attacks)

PV206 Communication and Soft Skills

zk 3/2 4 kr., podzim

• prof. Renate Motschnig - doc. RNDr. Tomáš Pitner, Ph.D.
• Prerequisities: SOUHLAS
  When writing the course application, describe your personal motivation. Tell us why you want to study soft skills in general (not this particular course), and your opinion on what part of the course you think will be useful to you. There is also an FAQ in Study materials that must be read by all students of the course; we recommend to read it even before writing your application.
• Goals: The primary goal of this course is to allow students to improve their competence in communication, teamwork, moderation and other soft skills based on the students’ actual demands.
  In the course, the students will gain knowledge and competencies regarding active listening, person centered communication, moderation techniques, team development, conflict management and related issues.
• Learning outcomes: After completion of the course, the students will be able to:
  - competently communicate in their profesional life;
  - actively participate in teamwork;
  - moderate events and activities;
  - use other soft skills based on the students’ actual demands;
  - listen actively;
  - do person centered communication;
  - master moderation techniques;
  - contribute to team development;
  - resolve conflicts and related issues.
• Syllabus: Communication theories
  Moderation techniques
  Levels of learning: knowledge, skills, attitudes
  Active Listening
  Person Centered Communication
  Groups and teams: group process, team building, self managed teams
  Conflict management and transformation
  Other topics according to the participants’ expectations

PV206 Communication and Soft Skills

zk 3/2 4 kr., jaro

• prof. Renate Motschnig - doc. RNDr. Tomáš Pitner, Ph.D.
• Prerequisities: SOUHLAS
  When writing the course application, describe your personal motivation. Tell us why you want to study soft skills in general (not this particular course), and your opinion on what part of the course you think will be useful to you. There is also an FAQ in Study materials that must be read by all students of the course; we recommend to read it even before writing your application.
• Goals: The primary goal of this course is to allow students to improve their competence in communication, teamwork, moderation and other soft skills based on the students’ actual demands.
  In the course, the students will gain knowledge and competencies regarding active listening, person centered communication, moderation techniques, team development, conflict management and related issues.
• Learning outcomes: After completion of the course, the students will be able to:
  - competently communicate in their profesional life;
  - actively participate in teamwork;
  - moderate events and activities;
  - use other soft skills based on the students’ actual demands;
  - listen actively;
  - do person centered communication;
  - master moderation techniques;
  - contribute to team development;
  - resolve conflicts and related issues.
• Syllabus: Communication theories
  Moderation techniques
  Levels of learning: knowledge, skills, attitudes
  Active Listening
  Person Centered Communication
  Groups and teams: group process, team building, self managed teams
  Conflict management and transformation
  Other topics according to the participants’ expectations

PV207 Business Process Management

zk 1/1 3 kr., jaro

• Mgr. Jiří Kolář, Ph.D. - Mgr. Lubomír Hruban
• Prerequisities: souhlas
  A Basic knowledge of Business analysis and architecture of Information Systems, basics knowledge of Web Services and some high-level programming language (Java, .NET), English
• Goals: Main goal of the course is an introduction to essentials of Business Process Management (BPM) and Service-oriented Architecture. BPM is a complex discipline on the edge of Management and Information System development. Students will get familiar with most important concepts of BPM and related BPMS platforms including most recent standards for process modeling (BPMN 2.0), process execution, business rules and human interaction with processes. Both open-source and commercial BPMS are presented and utilized for team projects during the course (IBM BPM, jBPM, Bonita, BizAgi BPM etc.). Important part of the course is a comprehensive team project, where students practice their acquired knowledge.
• Learning outcomes: Student will understand essentials of Business Process Management (BPM) and Service-oriented Architecture and will be able to consider these aspects whenever needed.
• Syllabus: List of lectures and seminars:
  
  
  Lecture: Organisation
  Lecture: General BPM
  Seminar-session: BPMS BizAgi demo - showcast
  Lecture: BPMS + SOA, Teambuliding,
  Seminar-session: BPMS BizAgi - hands-on,Teambuliding
  Lecture: BPM adoption methodologies, Domain analysis
  Seminar-session: Domain & process analysis exercise,
  Lecture: BPMN basics , Homework assignment
  Seminar-session: BPMN modeling, Level 1
  Lecture: BPMN advanced & other process modeling, Level 2,3 Homework assignment
  Seminar-session: BPMN modeling
  Lecture: Best Practices, Petri nets
  Seminar-session: BPMN best practices/Level 3, Homework consutlations
  Lecture: BPMS Technology - jBPM
  Seminar-session: Homeworks, jBPM
  Lecture: BPMS Technology - IBM BPM
  Seminar-session: Hands-on technology
  Lecture: Intermezzo, Q&A, Common Mistakes
  Seminar-session: IBM BPM Hands-on technology
  Lecture: Bizagi - process execution
  Seminar-session: Bizagi
  Lecture: Project consultations,
  Seminar-session: Project consultations
  Defenses

PV209 Person Centered Communication

k 2/1 3 kr., jaro

• prof. Renate Motschnig - doc. RNDr. Tomáš Pitner, Ph.D.
• Prerequisities: Previous experience at the level of PV206 Communication and Soft-skills course or similar is highly recommended. A teacher’s approval is required.
• Goals: The primary goal of this course is to allow students to communicate more sensitively and effectively. The students will learn how to listen actively and to express oneself in ways that facilitate understanding.
  Course goals in details: General. Participants acquire personal experience, skills, and background knowledge in situations of professional and everyday communication (such as listening, articulating, speaking in a group, conflict resolution, decision making, etc.). Participants build a learning community around the concern for better communication and understanding. Level of knowledge and intellect. Students acquire knowledge about the basics of the Person Centered Approach and Person Centered Encounter Groups. Level of skills and capabilities. Students gain active listening skills and improve their abilities in spontaneous communication and decision making in a group setting. Level of attitudes and awareness. Students gain self-experience while expressing own feelings, meanings, and intentions and perceiving those of others. They experience active listening and develop their own attitude towards it. Students become more sensitive and open to their own experience and loosen preconceived, rigidly held constructs. Students move towards acceptance and better understanding of themselves and others. Students move from more stereotyped behavior and facades to more personal expressiveness.
• Learning outcomes: After a successful completion of the course, the students will be able to:
  - professionally communicate using capabilities such as active listening, articulating, speaking in a group, resolve conflicts, make decisions;
  - express oneself in ways that facilitate understanding;
  - explain principles of Person Centered Approach and Person Centered Encounter Groups and apply them;
  - spontaneously communicate and make decisions in a group setting;
  - gain self-experience while expressing own feelings, meanings, and intentions and perceiving those of others;
  - become more sensitive and open to their own experience and loosen preconceived, rigidly held constructs;
  - move from more stereotyped behavior and facades to more personal expressiveness.
• Syllabus: Person Centered Communication; Active Listening; Congruence, acceptance, empathic understanding; Person Centered Encounter Groups: group process; Decision making, conflict, reflection
  Theoretical background: Person Centered Approach by Carl Rogers; Person centered, technology enhanced learning as developed at the Research Lab for Educational Technologies at the University of Vienna, Austria
  Learning Methods: Group dialog; Self experience; Reflection, self evaluation; Literature study

PV211 Introduction to Information Retrieval

zk 2/1 3 kr., jaro

• doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: Curiosity and motivation to retrieve information about information retrieval. Chapters 1--5 benefit from basic course on algorithms and data structures. Chapters 6--7 needs in addition linear algebra, vectors and dot products. For Chapters 11--13 basic probability notions are needed. Chapters 18--21 demand course in linear algebra, notions of matrix rank, eigenvalues and eigenvectors.
• Goals: Main objectives of this course is to introduce principles of information retrieval and gat acquainted with algorithms for NLP-based text processing.
• Learning outcomes: Students will understand document preprocessing, indexing, and querying done on up to a web scale (as Google does);understand principles and algorithms of NLP-based text preprocessing, text semantic filtering and classification, and web searching needed for information systems and digital library design.
• Syllabus: Boolean retrieval; The term vocabulary and postings lists
  Dictionaries and tolerant retrieval
  Index construction, Index compression
  Scoring, term weighting and the vector space model
  Computing scores in a complete search system
  Evaluation in information retrieval
  Relevance feedback and query expansion
  XML and MathML retrieval
  Text classification with vector space model
  Machine learning and information retrieval
  Hierarchical clustering
  Matrix decompositions and latent semantic indexing
  Web search basics
  Web crawling and indexes
  Link analysis, PageRank
  Invited lectures on related topics: image indexing, machine learning to rank, deep learning approaches, or even gait recognition.

PV212 Readings in Digital Typography, Scientific Visualization, Information Retrieval and Machine Learning

k 0/2 2 kr., podzim

• doc. RNDr. Petr Sojka, Ph.D.
• Prerequisities: souhlas
  Interest in research problems in areas of Machine Learning, Scientific Visualization, Information Retrieval and Digital Typography. Courage to learn how to move the human knowledge and understanding in these areas by CS research. Willingness to study particular topic of choice, and refer, discuss and brainstorm about it with others.
• Goals: The aim of the seminar is to give floor to students (both pregradual and gradual) to read, practice and present scientific results (eitheir their or those ackquires from scientific papaers. Every student will have her/his own presentation in the seminar.
• Learning outcomes: At the end of the course students will have experience in presenting and discussion of their or other (from readings) research. They also will be able to prepare scientific presentation of their work (slides, thesis), and communicate scientific results.
• Syllabus: Referred topics/projects for every year will be posted on the web page of the course, and negotiated with registered students. The lectures consist mostly of students' presentations. The presentations and discussion are in English. The students will have an ample space in the discussions after each presentation.

PV214 IT Service Management based on ITIL

zk 2/0 2 kr., podzim

• doc. Mouzhi Ge, Ph.D. - Ing. Aleš Studený
• Prerequisities: No pre-requisities are compulsory. It is recomended to have earned credits in SSME obligatory subjects.
• Goals: The course responds to the growing trend of world order, when everything will be provided in the form of services. This trend is evident in all sectors, but the most in the IT industry. Best practices providing IT services have been drawn up together with many professionals in the publications of the ITIL (Information Technology Infrastructure Library), which is based on the world standard ISO/IEC 20000.
  Students can get acquainted with theoretical knowledge and practical experience of how to manage the delivery of IT services. This experience may apply not only to manage internal IT, but also for the management of IT companies. These principles can apply as well as in the management of any other organization whose goal is to deliver the service.
• Learning outcomes: At the end of the course students should be able to: understand and explain the basics of IT Service Management and discover the importance of a systematic approach to management based on Information Technology Infrastructure Library (ITIL).
• Syllabus: 1. An introduction to ITSM
  - An introduction to ITSM and ITIL history
  - Difference between ITIL V2 and ITIL V3
  - ITSM/ITIL terminology basic
  - Related methodology: CobiT, MOF
  - Basic overview of ISO/IEC 20000
  - Essential ITSM support tools: Configuration Management Database
  - CMDB, Service Desk - SPOC, Event Management
  
  2. Basic processes, functions and roles
  - General principle: PDCA
  - A quick overview of ITSM: Service Strategy, Service Design, Service Transition, Service Operation, and Continual Service Improvement
  - Main processes: Incident Management, Event Management, Problem Management, Request Fulfillment, Access and Identity Management
  - Function
  - Roles
  
  3. Service Asset & Configuration Management SACM
  - Configuration Management System CMS
  - Configuration Management Database CMDB
  
  4. Release management / Software Licenses
  - Terms and definitions
  - Deployment options: Big Bang + Pull/Push
  - SW license
  - Legal perspective in the Czech Republic
  - SW management processes
  - Basic overview of ISO/IEC 19770
  
  5. Change Management
  - Levels of Change Management
  - Request Fulfillment
  - Terms and definitions
  - Function
  - Roles)
  
  6. Knowledge Management KB
  - Knowledge Management Processes
  - Terms and definitions
  - The basic rules and principles DIKW
  - Views: Internal Team, End User, Red Book
  
  7. IT strategy and Service strategy
  - Service Strategy Processes
  - Practice of Service Strategy
  - ITIL and Service Lifecycle
  - Processes: ITSM: Service Strategy, Service Design, Service Transition, Service Operation, and Continual Service Improvement
  - Service Capacity and Continuity Management
  - Information Security Management
  
  8. Service Level Management
  - Terms and definitions
  - Contracts with the customer
  - Contracts with suppliers - internal and external
  - Measuring availability and its aspects
  - Ways how to measure
  
  9. Reporting
  - Terms and definitions
  - Reporting vs. Analysis
  - Views: CIO / IT pros / Business
  - Examples of reports
  - The most important key performance indicators (KPIs) and critical success factors CSF
  
  10. Financial Management for IT Services
  - Financial Management
  - IT cost tracking
  - Methods of accounting for IT services
  - Budgeting Methods: IT Cost / IT Service Cost
  - IT Cost Center: Expense vs. Revenue Model
  
  11. ITSM implementation in practice
  - The main principles of management ITSM processes
  - The main principles of ITSM management projects
  - Pitfalls in implementing ISO/IEC 20000
  

PV215 Management by Competencies

zk 2/1 3 kr., jaro

• Ing. Leonard Walletzký, Ph.D.
• Prerequisities: No pre-requisities are compulsory. It is recomended to have earned credits in SSME obligatory subjects.
• Goals: The course introduces main aspects, which cause the problems of company management. It explains the methods and tools for identification and elimination of such problems through the management by competencies.
• Learning outcomes: At the end of the course students should be able:
  to understand management processes;
  to understand enterprise organization;
  to be able to identify business needs;
  to use theory of organization vitality;
  to understand duality between the world of requirements and the world of the posibilities.
• Syllabus: Introduction and motivation
  Management in company
  Company environment
  SWOT analysis
  Management by competencies
  Theory of vitality
  Company culture and pyramid of culture
  Strategic orientation of company
  Strategic continuum
  Processes and resources management
  Learning Organization

PV216 Marketing Strategy in Service Business

zk 1/1 3 kr., jaro

• Luca Carrubbo, Ph.D. - doc. Mouzhi Ge, Ph.D.
• Prerequisities: No pre-requisities are compulsory. It is recomended to have earned credits in SSME obligatory subjects.
• Goals: The course will introduce a concept of the shift to the service-oriented economy paradigm. The stress of seminars will be laid on practical team work and case studies analysis from domain of information technologies.
• Learning outcomes: At the end of the course students should be able:
  to understand marketing strategies of business organizations;
  to understand marketing strategies within the scope of new service paradigm;
  to manage marketing strategies processes from the project management point of view.
• Syllabus: Service-oriented economy paradigm
  Understanding service, markets, products and customers
  Building the service model
  Cooperation with customers
  Promoting the Value Proposition
  Positioning services in markets
  Blue Ocean Strategy
  Service environment
  Managing people for Service environment
  Win-win strategies

PV217 Service Oriented Architecture

k 2/0 2 kr., podzim

• Bruno Rossi, PhD
• Prerequisities: No prerequisites are compulsory.
• Goals: The objectives of the course are to give the students a set of skills necessary to understand and work in the context of Service Oriented Architectures (SOA), namely:
  - review several issues in the business adoption of SOA in an IT context;
  - give an understanding of the several definitions of SOA (as an architectural style, as an IT paradigm, ...);
  - review approaches for Service Oriented Analysis and Design and how they differ from Object Oriented analysis and Design;
  - review major standards in WSDL-*, together with SOAP and REST concepts;
  - present concepts such as orchestration, choreography, atomic transactions, message exchange patterns;
  - review major patterns in SOA in terms of security, reliability, maintainability of the implemented solutions;
  - review major parts of the SOA architecture, such as Enterprise Service Bus (ESB) and solutions provided by different vendors;
  - understand the differences between several architectural styles: monolith, SOA, microservices;
  - practice with the creation of microservices to better understand the concepts seen during the lectures;
• Learning outcomes: At the end of the course students will be able to:
  - explain the meaning of the "Service Oriented" paradigm both from the business and technical point of view;
  - understand the applicability of SOA design patterns and the meaning of the major SOA implementation technologies;
  - compare SOA with other architectural paradigms;
  - analyse requirements towards the creation of a service;
  - design a service starting from the analysis phase;
  - understand the problematics in service design and analysis;
  - understand the problematics in service implementation;
  - being able to classify and make reasoned decision about the adoption of different SOA platforms;
  - know how to implement a microservices-based system;
• Syllabus:
• Introducing service oriented architecture (SOA): SOA definition and concepts, Web services definition;
• Basics of SOA - Characteristics of SOA - Comparing SOA to client-server and distributed internet architectures - Anatomy of SOA - How components in an SOA interrelate. Principles of service orientation. Monolith vs SOA vs Microservices;
• SOA business aspects: standards of Web services, implementation SOA using Web services, business aspects of SOA and Web services;
• SOA Design Patterns: patterns for performance, scalability, and availability; Service Consumer patterns; Service integration patterns; SOA anti-patterns;
SOAP - Message exchange Patterns - Coordination - Atomic Transactions - Business activities - Orchestration - Choreography - Service layer abstraction - Application Service Layer - Business Service Layer - Orchestration Service Layer;
• Representational State Transfer (REST);
• Business-centric SOA - Deriving business services - service modelling - Service Oriented Design - Entity-centric business service design - Application service design - Task centric business service design;
• SOA Technologies - SOA Tooling - SOA Vendors;
• Microservices: task granularity, services organization, component sharing, message exchange, main principles. Technologies for microservices implementation. Using Quarkus to create microservices;

PV219 Webdesign seminar

k 0/2 2 kr., jaro

• RNDr. Tomáš Obšívač - doc. Ing. Michal Brandejs, CSc.
• Prerequisities: PV005
  Personal experience with the Web design is expected. Seminar is not for beginners.
• Goals: Main goal of the seminar is to get acquainted with internet presentation and web application life cycle through practice. Emphasis will be put on proper design, desirable implementation methods (e.g. observance of standards), operation aspects, monitoring, web effectiveness evaluation, propagation, advancement and redesign. Actual trends and near future of the WWW will be also discussed during workshop.
  Student by working during class will:
  – extend overview of developement and operation of web site,
  – gain deeper knowledge of selected topic, which he or she choose to present to the others,
  – develop skills in implementation of web technologies by hands-on approach,
  – familiarizes with tools, programs and principles which helps to webdesigner,
  – have the possibility to practice teamworking on given task,
  – may gain feedback to own existing project if he or she introduce it to the rest of group.
• Learning outcomes: Upon completion of the seminar, the student will better understand a number of activities from the design and implementation of modern web sites; will be capable of effective professional communication with specialists in the area of web design and development; and will understand and be able to solve problems in the chosen field.
• Syllabus: Website goals, initial analyses, Information Architecture
  Webpages layout, grids, wireframes, navigation
  Copywriting, typography on the web
  HTML and DOM
  CSS, graphic and interaction design
  Multimedia on the Web
  Usability (testing), User eXperience
  Accessibility (rules)
  Web Analytics
  Internet marketing, SEO, PPC, Content Strategy
  Server-side scripts, web frameworks, ready-made applications
  Basic principles with examples (session, database, templates, ...) given in PHP or another scripting language
  Content management systems
  Content sharing (providing and integration)
  Domain acquiring and web or application hosting
  JavaScript, interactivity, AJAX
  Web server, HTTP (authentication, cookies, status codes)
  Trends on the web (semantics, mashups, HTML 5, geolocation)

PV222 Security Architectures

k 3/1 2 kr., jaro

• Dr. Geraint Price - prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
• Prerequisities: PV017 || PV079 || PV157 || IV054 || souhlas
  Any of the following security/crypto courses: PV017||PV079||PV157||IV054
• Goals: This course will cover a number of topics related to the design and implementation of security architectures. The course content will broadly cover the following topics: access control mechanisms; web security; wireless LAN security; mobile (GSM & UMTS) security; identity management. The aim in each of these sessions will be to concentrate on how the security services in the architectures are constructed from underlying technical mechanisms. In addition, we will consider how the implementation of these mechanisms are not always perfect in real world implementations, and how the business requirements of an organisation can impact how we implement security.
• Syllabus: This course will cover a number of topics related to the design and implementation of security architectures. The course content will broadly cover the following topics: access control mechanisms; web security; wireless LAN security; mobile (GSM & UMTS) security; identity management. The aim in each of these sessions will be to concentrate on how the security services in the architectures are constructed from underlying technical mechanisms. In addition, we will consider how the implementation of these mechanisms are not always perfect in real world implementations, and how the business requirements of an organisation can impact how we implement security.

PV225 Laboratory of Systems Biology

k 1/2 3 kr., podzim

• prof. Ing. Miloš Barták, CSc. - doc. RNDr. David Šafránek, Ph.D.
• Prerequisities: There are no preconditions. Students are expected to be interested in overlapping disciplines combining Biology and Informatics.
• Goals: At the end of the course students should be able to: understand physiology of plants and bacteria at very elementary level; understand most important methods of experimental measuring; measure data using particular techniques; summarize and interpret the measured data.
• Learning outcomes: At the end of the course students should be able to:
  - interpret basic aspects of physiology of plants and bacteria at elementary level;
  - solve problem of parameter identification of a model with respect to experimental data;
  - select and use a suitable tool for parameter identification;
  - process a set of experimentally measured data for use in a suitable tool.
• Syllabus: I Metabolomics
  I.1 Metabolomics (Introduction; Metabolites; Metabolite Fingerprinting and Footprinting; Metabolite Profiling; Target-based analysis of metabolites)
  I.2 Role of metabolomics in Systems Biology (Microbial metabolomics; Plant metabolomics; Human metabolomics)
  I.3 Assey preparation (Obtaining media; Stopping of metabolism)
  I.4 Methods used in metabolomics
  I.5 Metabolomic data analysis
  
  II Photobiology
  II.1 Photochemical processes in photosynthesis
  II.2 Role of photosynthesis in Systems Biology
  II.3 Theoretical foundations of Fluorometrics
  II.4 Methods of induced fluorescence
  II.5 Obtaining and analysis of fluorometrics data

PV226 Seminar LaSArIS

z 0/2 2 kr., podzim

• RNDr. Radek Ošlejšek, Ph.D. - doc. RNDr. Tomáš Pitner, Ph.D. - doc. Ing. RNDr. Barbora Bühnová, Ph.D. - Bruno Rossi, PhD - Ing. Lukáš Grolig
• Prerequisities: SOUHLAS
  Basic experience with implementation of nontrivial program systems. Interest in Lasaris activities.
  In the case of Process Mining seminar (see Course objectives), the interest about the data science and this particular domain is enough.
  In the case of Blockchain seminar (see Course objectives), students must have solid skills in programming with C++ or Java languages and have good knowledge of working on a Linux desktop. It is necessary to have the laptop with installed Linux.
• Goals: Learning outcomes of the course unit The aim of the course is to support the activities of the Laboratory of Software Architectures and Information Systems (Lasaris) in research, development and teaching of theoretical topics and practical problems in building large software systems and deployment of modern information technologies in practice. It deals with the design and development of reliable and secure information systems, process and data modeling, system implementation management, and software technologies for their construction. The seminar makes acquainted with interesting research and development projects solved in Lasaris, particularly in the area of designing large IT and critical infrastructures, for example, to support smart grids. Additionally, external specialists, especially from the IT industry or from abroad, are regularly invited to talk.
  
  In the autumn 2020 semester, PV226 will host separate semester specialized seminars conducted in English or Czech / Slovak. Those interested in one of them enroll in the course PV226 and select the appropriate seminar group:
• Process Mining led by Martin Macák, in which you will learn about many techniques of process analysis based on recorded events.
• Blockchain (led by Dr. Bacem Mbarek) focused on understanding the concepts of Blockchain, design and implementation of selected Blockchain use cases, creating smart contracts and deploying IoT networks via Hyperledger Fabric Compose.
• IoT (led by Ing. Lukáš Grolig) focused on the basics of Internet of Things technologies incl. necessary introduction to microelectronics.
• Machine Learning (led by Ing. Lukáš Grolig) focused on the practical application of machine learning in the real world.
  
  More information at https://lasaris.fi.muni.cz/students/teaching/pv226
• Learning outcomes: Student will be able to:
  - actively participate in the activities of the Software Architecture and Information Systems Laboratory (Lasaris) research, development and teaching of topics related to the theoretical solutions practical problems in building large software systems and the deployment of modern information technology in practice;
  - apply the chosen knowledge of the design and development of reliable and secure information systems, process and data modeling, system implementation management, and software technologies for their construction;
  - engage in research and development projects in Lasaris, particularly in the area of designing large IT and critical infrastructures, for example, to support smart grids.
• Syllabus: Lasaris basic seminar:
• Software architectures
• Technology
• Information systems and management
• Critical Infrastructure Protection
  
  For specialized seminar groups on Process Mining, Blockchain, Machine Learning and IoT, see https://lasaris.fi.muni.cz/students/teaching/pv226

PV226 Seminar LaSArIS

z 0/2 2 kr., jaro

• doc. Ing. RNDr. Barbora Bühnová, Ph.D. - doc. RNDr. Tomáš Pitner, Ph.D. - RNDr. Radek Ošlejšek, Ph.D. - Bruno Rossi, PhD
• Prerequisities: SOUHLAS
  Basic experience with implementation of nontrivial program systems. Interest in Lasaris activities.
  In the case of Process Mining seminar (see Course objectives), the interest about the data science and this particular domain is enough.
  In the case of Blockchain seminar (see Course objectives), students must have solid skills in programming with C++ or Java languages and have good knowledge of working on a Linux desktop. It is necessary to have the laptop with installed Linux.
• Goals: Learning outcomes of the course unit The aim of the course is to support the activities of the Laboratory of Software Architectures and Information Systems (Lasaris) in research, development and teaching of theoretical topics and practical problems in building large software systems and deployment of modern information technologies in practice. It deals with the design and development of reliable and secure information systems, process and data modeling, system implementation management, and software technologies for their construction. The seminar makes acquainted with interesting research and development projects solved in Lasaris, particularly in the area of designing large IT and critical infrastructures, for example, to support smart grids. Additionally, external specialists, especially from the IT industry or from abroad, are regularly invited to talk.
  
  In the spring 2020 semester, PV226 hosts an autonomous specialized seminar Process Mining, in which you will learn many techniques for the analysis of processes based on the recorded events. Martin Macák will be in charge of this seminar.
  
  In the spring 2020 semester, PV226 hosts an autonomous specialized seminar Blockchain. Through this course, students will be provided with a comprehensive understanding of Blockchain. They will learn the methods of securing distributed ledgers. They will also learn the design and implementation of selected Blockchain use-cases. In addition to developing cases of smart contracts, students will work on deploying an Internet of Thing (IoT) network where Blockchain is integrated using a dedicated tool, such as Hyperledger Fabric Composer. Bacem Mbarek in cooperation with Martin Macák will be in charge of this seminar.
• Learning outcomes: Student will be able to:
  - actively participate in the activities of the Software Architecture and Information Systems Laboratory (Lasaris) research, development and teaching of topics related to the theoretical solutions practical problems in building large software systems and the deployment of modern information technology in practice;
  - apply the chosen knowledge of the design and development of reliable and secure information systems, process and data modeling, system implementation management, and software technologies for their construction;
  - engage in research and development projects in Lasaris, particularly in the area of designing large IT and critical infrastructures, for example, to support smart grids.
• Syllabus: In case of Lasaris (basic seminar):
  Area Software architectures
  Area Technology
  Area Information systems and management
  Area Applications
  
  In the case of Process Mining seminar:
  Data Mining
  Process Models and Process Discovery
  Different Types of Process Models
  Process Discovery Techniques and Conformance Checking
  Enrichment of Process Models
  Operational Support
  
  In the case of Blockchain seminar:
  Blockchain
  Smart contract
  Blockchain framework implementation (Hyperledger Fabric)
  Security and Privacy
  Hyperledger caliper: Blockchain Simulator
  Internet of things

PV227 GPU Rendering

k 0/2 2 kr., podzim

• RNDr. Jan Byška, Ph.D. - RNDr. Jan Čejka - Mgr. Jiří Chmelík, Ph.D. - Mgr. David Kuťák
• Prerequisities: PV112
  Knowledge of C/C++ programming language. Knowledge of OpenGL in the scope of the course PV112 Computer Graphics API.
• Goals: This lecture aims to give an overview of the basic GPU programming methods and commonly used techniques with the focus on shader programming. Students: will gain practical knowledge of GPU programming; will understand the workflow of special purpose high-level programming languages; will be able to write parallel programs running on the GPU;
• Learning outcomes: At the end of the semester, a student should be able to:
  - understand and describe possibilities of modern programmable GPUs for rendering 3D scenes;
  - read up a and explain function of existing GLSL shaders;
  - design and implement own GLSL shaders
• Syllabus: Programmable graphics pipeline.
  Shadows
  Deferred shading
  SSAO, DoF
  HDR, bloom
  Particle systems, compute shaders
  Geometry shaders
  Tessallation shaders
  Microfacets
  Physically Based Rendering, IBL
  Vulkan
  Parallax Occlusion Mapping

PV229 Multimedia Similarity Searching in Practice

z 0/2 2 kr., jaro

• RNDr. Michal Batko, Ph.D.
• Prerequisities: PA128 || NOW ( PA128 )
  Basic programming skills in Java language (course PB162 is recommended)
• Goals: To goal of this course is to introduce main problems and common solutions of multimedia search engines.
• Learning outcomes: On successful completion of the course students will be able: to understand cutting-edge technologies for multimedia search; to design multimedia search engines; to implement a search engine prototype including data preparation, performance tuning, and visualization of results via user interface.
• Syllabus: Introduction, demonstration of the MUFIN system, setup of the development environment
  Data collections and similarity functions
  Extraction of multimedia data descriptors
  Executing search algorithms on data collections, a command line interface
  Using search engine operations – insertions, deletions, queries
  Preparing command batches – bulk data insertion, automatic searching, statistics
  Data storage
  Pivot selection techniques
  Using advanced index algorithms – listing available implementations, getting/setting index parameters
  User and application interfaces

PV233 Networks and Routing Protocols

zk 2/2 3 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D. - Mgr. Luděk Bártek, Ph.D. - Ing. Mgr. et Mgr. Zdeněk Říha, Ph.D. - doc. Ing. Jaroslav Dočkal, CSc. - Ing. Josef Kaderka, Ph.D.
• Prerequisities: ( PB156 || PV183 ) && SOUHLAS
  
• Goals: This course covers the architecture, components, and operations of routers and switches in larger and more complex networks. Students learn how to configure routers and switches for advanced functionality. The main goal of the course Networks and Routing Protocols is to provide students with information on modern computer networks and allow them to acquire practical skills for building and managing computer networks. During the course, students will be acquainted with the OSI reference model layers (their functionality and protocols), Ethernet network architecture, issues of static and dynamic routing (protocols RIPv1, RIPv2, EIGRP, and OSPF), and with IOS operating system.
• Learning outcomes: After finishing this course the student:
  will know the principles of computer network communication;
  will understand the layers of ISO/OSI models, their purpose, functions, and protocols used on a particular layer;
  will be able to build Ethernet based networks;
  will know the principles of static routing;
  will know the dynamic routing protocols;
  will be able to configure Cisco switches and routers in small to medium-sized networks.
• Syllabus: Switched networks and switches
  Virtual LANs
  Static and dynamic routing
  RIP, RIPng, OSPF protocols(a single area)
  Routing tables
  Access control lists (ACL)
  DHCP protocol
  Network Address Translation in IPv4

PV234 LAN Switching and Wireless Networks, WAN

zk 2/2 3 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D. - Mgr. Luděk Bártek, Ph.D. - Ing. Mgr. et Mgr. Zdeněk Říha, Ph.D. - doc. Ing. Jaroslav Dočkal, CSc. - Ing. Josef Kaderka, Ph.D.
• Prerequisities: PV233 && SOUHLAS
  
• Goals: The main goal of the course LAN Switching and Wireless Networks, WAN is to provide students with information on modern computer networks and allow them to acquire practical skills for building and managing computer networks. During the course, students will be acquainted with the principles and management (configuration) possibilities of switched local area networks and wireless local area networks. The attention will also be paid to the access to wide area computer networks and to security issues.
• Learning outcomes: At the end of this course, students will:
  be able to operate Cisco switches;
  be able to create and configure virtual local area networks;
  know the STP and VTP concepts;
  be able to manage and configure wireless local area networks;
  have knowledge from the area of wide computer networks;
  be familiar with the principles of point-to-point communication;
  know the Frame Relay technology;
  have a basic knowledge of computer networks security;
  be able to configure NAT, DHCP, and RIP for IPv6.
• Syllabus: Redundancy and link aggregation in LAN networks
  Wireless LAN (WLAN)
  OSPF protokol(multiple areas)
  EIGRP protocol
  Advanced configuration
  Operating system manipulation and licensing
  
  Global computer networks
  Point-to-point networks
  Frame Relay protocol
  Fast network services
  Securing communication between networks
  Computer network monitoring
  Troubleshooting

PV236 Time Management and Effectiveness

k 2/0 2 kr., podzim

• Ing. Michala Kozinová
• Prerequisities: PA180 || PA186 || NOW ( PA180 )|| NOW ( PA185 )|| NOW ( PA186 )
  In parallel with PA180 or PA185/PA186 Interim Project (recommended) or after the completion of Interim Project
• Goals: At the end of the course, the students should be able to:
  Actively keep in mind efficiency and effectiveness when dealing with day-to-day situations.
  Use task lists, organize their time, and understand the way they prioritize.
  Make responsive decisions.
  Handle complex situations as a project.
  Understand the importance of planning, contingency, and expectations management.
  Run effective meetings with clear agenda, outcomes, commitments, owners, and deadlines.
  Apply the principles of effective problem solving.
  Respect the rules of effective communication.
  Write concisely.
  Delegate.
  Confidently provide and accept feedback to prevent obstacles of cooperation.
  Understand the basic principles of communication in crisis.
  Handle the life under SLAs.
• Learning outcomes: At the end of the course, the students should be able to:
  Actively keep in mind efficiency and effectiveness when dealing with day-to-day situations.
  Use task lists, organize their time, and understand the way they prioritize.
  Make responsive decisions.
  Handle complex situations as a project.
  Understand the importance of planning, contingency, and expectations management.
  Run effective meetings with clear agenda, outcomes, commitments, owners, and deadlines.
  Apply the principles of effective problem solving.
  Respect the rules of effective communication.
  Write concisely.
  Delegate.
  Confidently provide and accept feedback to prevent obstacles of cooperation.
  Understand the basic principles of communication in crisis.
  Handle the life under SLAs.
• Syllabus: Efficiency and effectiveness
  Prevention and Planning
  Prioritization
  Effective communication
  Management of expectations
  Effective meetings
  Problem solving and Critical reasoning

PV237 Strategy and Leadership

k 2/0 4 kr., jaro

• Ing. Michala Kozinová - doc. RNDr. Tomáš Pitner, Ph.D.
• Prerequisities: No pre-requisities are compulsory.
• Goals: - Equip student with thoughts and concepts they can build on to become world-class leaders and people managers. - Have students get close to the real-life experience in strategic decision making in a tough competitive environment via GLo-bus strategic simulation game. The students will be hired as co-managers at year 5 of a successful global company to meet a set of goals in year 11: Grow earnings per share, grow return on equity, achieve stock price gains, and maintain healthy credit and image rating. The students will thus familiarize themselves with strategic planning in the global company mastering marketing and financial cause-effect relations. - Prepare students for the challenges related to change management. - Make sure graduates can easily participate in strategic discussions by knowing the most common concepts and tools. - Forewarn is forearmed - create general awareness of decision making bias.
• Learning outcomes: Students will be prepared to accept greater responsibility in our society.
• Syllabus: PV237 Strategy and Leadership The course consists of 3 major blocks - Strategy, Leadership, and, since Leadership is the ability to get followed through the change, Change Management. The course delivers only as much theory as the graduates are likely to meet and need in the business world and students are encouraged to figure the theoretical concepts themselves wherever possible. The course will be delivered via lectures, workshops, brainstorming sessions and class discussion. In 2017, we will pilot global Strategic simulation game Glo-bus, where about 30 hours of students' time will be required outside of the class.

PV239 Mobile Application Development

k 2/1 4 kr., jaro

• doc. Ing. RNDr. Barbora Bühnová, Ph.D.
• Prerequisities: PV256 || SOUHLAS
  Advanced knowledge of programming that should be detailed in the request for course enrolment. The request should also mention the platform that the student prefers and their motivation for course enrolment.
• Goals: The course focuses on concepts of the mobile application development, which is a modern and current trend of software development. Within the course, mainly particular specifics and concepts of mobile platforms will be introduced. Furthermore, architecture and development principles for Google Android, Apple iOS (iPhone/iPad) and Xamarin (multi-platform development) will be presented. Finally, teams of students will work on a project - a mobile application - that help them understand design and development of mobile applications in practice.
• Learning outcomes: At the end of this course the student will:
  - know the tasks, tools and techniques accompanying the development process of mobile applications;
  - know specifics of the major mobile platforms - Android and iOS - and multi-platform development with Xamarin;
  - be familiar with Android Studio (for Google Android), XCode (for iOS application), and Visual Studio (for Xamarin) in all important aspects.
• Syllabus: Introduction to the development and specifics of mobile platforms
  Programming concepts, architecture and SDK for the Android platform
  Programming concepts, architecture and SDK for the iOS platform
  Concepts of multi-platform development and the Xamarin platform
  Basics of user interface design for mobile devices
  Mobile platform security
  Project

PV240 Introduction to service marketing

zk 2/0 3 kr., podzim

• doc. Mouzhi Ge, Ph.D. - Ing. Leonard Walletzký, Ph.D.
• Goals: To give a comprehensive overview of the concept and content of service marketing. To develop a unified, primary knowledge required for university studies. During the course of the semester students will familiarize themselves with complex service marketing tools, their potential application and limitations. The course explains the role and the importance of the empirical data for forecasting desires and demands of consumers. Students will get insight into the practical gathering of information and their interpretation: the course leads the students through the process which starts with the formulation of the research question, continues with the collection and processing of data, and ends with the summary and evaluation of results.
• Learning outcomes: Student will understand:
  - how to design the marketing strategy
  - basic concepts of maketing mix
  - how to plan, realize and analyze the marketing survey - the ways of unusual ways of the marketing (guerilla marketing, niche marketing)
• Syllabus: 1. Basic principles and meanings of marketing (dotace 2/0)
  2. Marketing management (dotace 2/0)
  Marketing management
  Marketing strategies
  Marketing plan
  3. Marketing environment and portfolio analysis (dotace 2/0)
  4. Marketing information system (dotace 6/0)
  Marketing research problem
  Collecting data techniques and data processing
  Sampling and units of marketing research
  
  5. Marketing decisions (dotace 4/0)
  Consumer behaviour
  Segmentation
  6. Marketing mix (dotace 6/0)
  Product
  Price
  Place
  Promotion
  People
  7. Service marketing (dotace 2/0)

PV241 Enterprise and Financial Management

zk 2/0 2 kr., podzim

• Ing. David Fuchs - Ing. Leonard Walletzký, Ph.D.
• Goals: Interpretation focuses on the basic terminology, processes and linkages in the functioning of companies.
• Learning outcomes: Student understands basic terminology, processes and linkages in the functioning of business companies.
• Syllabus: Introduction to corporate finance; Financial decision-making; The property and financial structure of company; Financial analysis of the company; Company and financial market; The financing company; Cash flows in the company; Financial Planning; Risks of operating businesses; Distribution of profits; The value of the company; The company and the foreign exchange market

PV241 Enterprise and Financial Management

zk 2/0 2 kr., jaro

• Ing. David Fuchs
• Goals: Interpretation focuses on the basic terminology, processes and linkages in the functioning of companies.
• Learning outcomes: Student understands basic terminology, processes and linkages in the functioning of business companies.
• Syllabus: Introduction to corporate finance; Financial decision-making; The property and financial structure of company; Financial analysis of the company; Company and financial market; The financing company; Cash flows in the company; Financial Planning; Risks of operating businesses; Distribution of profits; The value of the company; The company and the foreign exchange market

PV242 Innovation and entrepreneurship

k 1/1 3 kr., jaro

• Ing. David Fuchs - RNDr. Vojtěch Krmíček, Ph.D. - Ing. Jitka Sládková, Ph.D. - Ing. Leonard Walletzký, Ph.D.
• Prerequisities: No pre-requisities are compulsory.
• Goals: The objective of the practical course is to give a basic orientation in the business area. It will bring information about appropriate procedures and proven tools. Further, the students will meet experts from different areas (IT, services, social business, production…)
  Lectures will be given through lecture form with small workshops during lessons (individual/in pairs). The course is suitable also for a large number of students.
• Learning outcomes: Student will gin knowledge needed for succesfull start of a small enterprise.
• Syllabus: 1. Introduction to entrepreneurship, personal vision and strenghts, meeting/sharing experience with successful businessman
  2. Lean methodology, market research, meeting/sharing experience with successful businessman
  3. Action plan, MVP, prototyping, FabLab visit
  4. Business model, financial analysis, pricing
  5. Intellectual property and its protection
  6. Presentation Skills

PV243 Advanced Java technologies: JBoss

zk 1/1 2 kr., jaro

• Mgr. Jiří Kolář, Ph.D. - Ing. Jiří Pechanec
• Prerequisities: PA165 || SOUHLAS
  Good command of Java at the level reached in the PB162 PA165 is required.
• Goals: Goal of this course is to make student familiar with advanced Java EE technologies, with news in Java EE 6 a and teach them about JBOss technologies and how to work with JBoss.org projects.
• Learning outcomes: Students should acquire knowledge about most recent technologies in Java EE and good overview over JBoss products.
• Syllabus: Intro into new features
  CDI, EJB 3.1
  Seam 3 (what is missing in CDI)
  Security in Java EE applications, JAAS
  Storage of data in a cloudu - Infinispan
  Clustering and scalability JBoss AS 7
  Management and monitoring of JBoss AS 7

PV244 Routing Services for Building Scalable Networks

zk 2/2 3 kr., podzim

• Ing. Josef Kaderka, Ph.D.
• Prerequisities: PV234 && SOUHLAS
  
• Goals: The aim of the course is to provide information on planning of services of large networks and ways to connect branche and mobile users. Students will get practical experience with configuration of networks connected via multiple routing protocols. During the course the students will work with EIGRP, OSPF and BGP protocols and will configure exachange of routing information between networks based on different routing protocols.
• Learning outcomes: At the end of the course the student will: know the principles of communications in complicated networks and know the methods how to solve data flows with complex requirements. The students will be able to configure complex tasks on Cisco routers.
• Syllabus: • Planning services of large networks • Advanced solutions based on EIGRP • Adcanced solutions based on OSPF with multiple areas • Mnipulation with routing information in redistribution • Implementation of path control • Routing based on policies and agreement on service levels • Connecting large networks to ISP. BGP protocol. • Implementation of IPv6 • Connecting branches and mobile users to corporate networks • Presentation of case studies • Final theoretical • Practical exam

PV245 Switching

zk 2/2 3 kr., jaro

• doc. Ing. Jaroslav Dočkal, CSc. - Ing. Josef Kaderka, Ph.D.
• Prerequisities: PV234 && SOUHLAS
  PV233, PV234, PV244
• Goals: Course PV245 - Enterprise Advanced Routing (ENARSI) provides students with an in-depth knowledge to support the implementation and troubleshooting of advanced routing technologies and services including layer 3 VPN services, infrastructure security and infrastructure services used in enterprise networks.
• Learning outcomes: By the end of the course, students will be able to: - Implement DHCP to operate across multiple LANs. - Implement EIGRP for IPv4 in a small to medium-sized business network. - Explain how advanced EIGRP features affect network performance. - Troubleshoot common EIGRP configuration issues. - Troubleshoot EIGRPv6 issues. - Explain how OSPF operates. - Implement multiarea OSPF for IPv4 to enable internetwork communications. - Troubleshoot connectivity issues in OSPFv2. - Implement multiarea OSPFv3. - Troubleshoot issues with OSPFv3 implementation. - Configure BGP. - Configure BGP with advanced features. - Explain the processes used by BGP for path selection. - Troubleshoot BGP issues. - Troubleshoot Route Maps and conditional forwarding issues. - Configure route redistribution between routing protocols. - Troubleshoot IPv4 and IPv6 route redistribution. - Explain the impact of VFR and MPLS on routing decisions. - Implement DMVPN tunnels. - Configure IPsec DMVPN with Pre-Shared Authentication. - Troubleshoot ACLs and Prefix Lists. - Troubleshoot security threats to a network. - Troubleshoot Device Management and Management Tools. This course is the 2nd of 2 courses in the Cisco CCNP Enterprise curriculum and includes hands-on lab work along with a wide array of assessment types and tools.
• Syllabus: IPv4/IPv6 Addressing and Routing Review
  EIGRP
  Advanced EIGRP
  Troubleshooting EIGRP for IPv4
  EIGRPv6
  OSPF
  Advanced OSPF
  Troubleshooting OSPFv2
  OSPFv
  Troubleshooting OSPFv3
  BGP
  Advanced BGP
  BGP Path Selection
  Troubleshooting BGP
  Route Maps and Conditional Forwarding
  Route Redistribution
  Troubleshoot Redistribution
  VRF, MPLS, and MPLS Layer 3 VPNs
  DMVPN Tunnel
  
  Securing DMVPN Tunnels
  Troubleshooting ACLs and Prefix Lists
  Infrastructure Security
  Device Management and Management Tools Troubleshooting

PV247 Modern Development of User Interfaces

z 0/3 3 kr., podzim

• Mgr. Patrik Majerčík - doc. RNDr. Tomáš Pitner, Ph.D. - Mgr. Martin Bokša - Mgr. Peter Halmo - Ing. Matej Tábi
• Prerequisities: SOUHLAS
  Basic knowledge of imperative and non-imperative programming. Basic knowledge of HTML and CSS is expected within the scope of PB138 Modern Markup Languages and Their Applications. Knowledge of Javascript, HTTP protocol and REST architecture is an advantage.
• Goals: Students will understand the basic principles of user interface development using modern tools. Upon successful completion of this course, the student is able to apply the principles of elaboration of semester project focused on user interface. The subject is mostly practical and students are expected to have pro-active approach.
• Learning outcomes: User interface development technologies are dynamic and therefore change very quickly. Student after successful completion:
  - has an overview of modern web development technologies and is able to use them in practice;
  - is familiar with the process of developing modern web applications using best practices.
• Syllabus: Introduction to the course content
  Introduction to JS, HTML, CSS
  Node and NPM - packaging system
  React - Basics
  React - Advanced
  React - Lifecycle in Class component
  Asynchronous operation
  React
  State management
  Deployment
  TypeScript
  React Native, Electron
  Future of React

PV248 Python

k 1/1 2 kr., podzim

• RNDr. Petr Ročkai, Ph.D.
• Prerequisities: Basic programming skills in Python (at least to the extent covered in IB111).
• Goals: The goal of this subject is to teach students the specifics of programming in Python, mainly on with practical exercises. During the semester, students will work on programming assignments, which will focus on the material covered in the lectures.
  By the end of the course, students will:
  * understand the basics of object-oriented design and implementation in Python
  * be acquainted with the standard library
  * understand the basics of problem decomposition and robust implementation
• Learning outcomes: Student will be able to:
  - program in the Python programming language
  - understand Python code written by others
  - find and use the information needed for Python development
  - test their programs written in Python
• Syllabus: 1. Introduction, text, regular expressions
  2. Objects and classes
  3. Testing and debugging
  4. Persistent data
  5. Working with numeric data
  6. Memory and data model
  7. Lambda, iteration, decorators
  8. Lexical closures, carcasses
  9. Modules and packages
  10. Concurrency, exceptions
  11. Communication, HTTP
  12. Asyncio Library

PV251 Visualization

zk 2/1 3 kr., podzim

• doc. RNDr. Barbora Kozlíková, Ph.D. - RNDr. Jan Byška, Ph.D.
• Prerequisities: No additional prerequisites.
• Goals: The goal is to provide students with the overview of the field of visualization and its principles and methods. The course includes basic concepts of visualization and its application to different input data sets. Students also will be acquainted with various interaction techniques for data manipulation and with practical applications of visualization, such as in medicine, art etc. An important part of this course contains practical exercises performed on various visualization tools. At the end of this course, students should be able to design and develop their own effective visualizations.
• Learning outcomes: After passing this course, the students will be able to: - evaluate the suitability of existing visualization techniques for a given task - determine the basic mistakes of existing visualization solutions - design appropriate visualizations for given tasks - implement an optimized solution of a selected visualization
• Syllabus: Introduction, history of visualization, visualization today, human perception and information processing
  Color, types of input data
  Visualization foundations
  Visualization techniques for spatial data
  Visualization techniques for geospatial data
  Visualization techniques for multivariate data
  Graphs and trees, networks
  Text and document visualization
  Interaction concepts and techniques
  Designing effective visualizations, comparing and evaluating visualization techniques
  Visualization tools and systems
  Specific applications of visualization - medical visualization, NPR, scientific visualization

PV253 Seminar of DISA Laboratory

k 0/2 2 kr., podzim

• prof. Ing. Pavel Zezula, CSc.
• Prerequisities: Students should be interested in cooperation on research projects conducted by the laboratory. The knowledge of English is necessary to study original research papers. Basic experience with programming and data management system implementations is an advantage.
• Goals: The course objective is a presentation of the state-of-the-art knowledge in research areas of the laboratory. A special emphasis is put on presentations of innovative ideas and proposals by researchers involved in current projects of DISA. The seminar is a source of new knowledge for students and other laboratory members and at the same time it forms a feedback for lecturers (prevalently project researchers). Short student presentations working on bachelor or master theses are also part of the course activities.
• Learning outcomes: Student will improve their presentation skills, and will undesrtand selected research results in the domain of the laboratory.
• Syllabus: The selection of presentations is based on research interests of ongoing projects. At the moment, the topics include:
  Similarity searching and filtering in multimedia data (mainly images and video);
  Searching for sub-images;
  Searching in large collections of biometric data;
  Similarity models of dynamic biometric characteristics (mainly human movements);
  Multimodal interpretation of multimedia data;
  Findability of multimedia data;
  Scalability for knowledge extraction and searching, etc.

PV253 Seminar of DISA Laboratory

k 0/2 2 kr., jaro

• prof. Ing. Pavel Zezula, CSc.
• Prerequisities: Students should be interested in cooperation on research projects conducted by the laboratory. The knowledge of English is necessary to study original research papers. Basic experience with programming and data management system implementations is an advantage.
• Goals: The course objective is a presentation of the state-of-the-art knowledge in research areas of the laboratory. A special emphasis is put on presentations of innovative ideas and proposals by researchers involved in current projects of DISA. The seminar is a source of new knowledge for students and other laboratory members and at the same time it forms a feedback for lecturers (prevalently project researchers). Short student presentations working on bachelor or master theses are also part of the course activities.
• Learning outcomes: Student will improve their presentation skills, and will undesrtand selected research results in the domain of the laboratory.
• Syllabus: The selection of presentations is based on research interests of ongoing projects. At the moment, the topics include:
  Similarity searching and filtering in multimedia data (mainly images and video);
  Searching for sub-images;
  Searching in large collections of biometric data;
  Similarity models of dynamic biometric characteristics (mainly human movements);
  Multimodal interpretation of multimedia data;
  Findability of multimedia data;
  Scalability for knowledge extraction and searching, etc.

PV254 Recommender Systems

k 1/1 2 kr., jaro

• doc. Mgr. Radek Pelánek, Ph.D.
• Prerequisities: Programming skills, mathematics at the level of MB101-MB104 courses.
• Goals: The goal of the course is to familiarize students with basic techniques and problems in the field of recommender systems. The course is project based - students have practical experience with development of a simple recommender system or with a partial evaluation of a realistic recommender system.
• Learning outcomes: At the end of the course students will understand the main types of recommender systems and their application domains; be able to apply the basic recommender techniques; be able to implement basic versions of recommender techniques; understand main aspects of evaluation of recommender systems and be able to analyze such evaluations.
• Syllabus: Recommender systems, motivation, applications in different domains.
  Types of recommender systems: non-personalized, content based, collaborative filtering.
  Techniques and algorithms for recommender systems, particularly with focus on collaborative filtering (user-user, item-item, SVD).
  Evaluation: methodology, types of experiments, evaluation metrics, examples.
  Other aspects of recommender systems (e.g., explanations of recommendations, trust, attacts).
  Case studies (e.g., Amazon, Netflix, Google News, YouTube).
  Educational recommender systems, current research at Faculty of informatics.

PV255 Game Development I

z 2/1 3 kr., podzim

• Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: PB009 && PV112 && ( PB161 || PB162 )
  Expected knowledge: - basics of 3D computer graphics (transformations in 3D space, textures, materials, local and global illumination, etc.) - basic knowledge of shader programming (what is vertex/fragment shader, how to use it) - object-oriented programming.
• Goals: The aim of the course is to introduce the field of development of digital games, both theoretical and practical approaches. At the end of the course students should be able to: the design concept of a simple digital game;
  design and create audio-visual content of the game;
  design and implement basic game mechanisms;
  compile and publish own digital game.
• Learning outcomes: At the end of the semester, a student should be able to:
  - create a design of digital game;
  - write down game design document;
  - implement a playable prototype of the game;
  - estimate time load of the project;
• Syllabus: Introduction, organization; From the concept to the final product.
  Game-play principles (strategy, fps, platformer, etc.), labour intensity of various game types. Motivation principles in games.
  Game design: game-play, aesthetics, game environment and levels. Relation between design and monetization.
  Principles of computer graphics in games: 3D models, LoD, sprites, culling, tessellation, procedural generation and instancing; Performance: polygon count, textures size, shaders.
  Physical simulations in games: collision detection, springs, rag-doll physics.
  Lighting: real-time lighting, static vs. dynamic lights, global illumination. Performance.
  Shaders and graphical effects in games: types of shaders (manipulation and coloring vertices, lighting, transparency, screen-space shaders).
  Animations: atomic animations, state automata, blending; relation between code and animations.
  Game interface: controls (keyboard, mouse, gamepad, touch screen, motion capture, VR); graphical user interface and menus (main, in-game, HUD).
  Artificial intelligence - principles: game-state, simulator, controllers; movement, path-finding, searching; perceiving, decision making, remembering, execution. AI data structures: state machines, path graphs, behavior trees, neural networks.
  Production: developers team, roles in team; financial aspects; online publishing and monetization options.

PV256 Introduction to Development for Android

k 2/2 3 kr., jaro

• RNDr. Bc. Jonáš Ševčík
• Prerequisities: PB162
  
• Goals: The aim of the course is to acquaint students with the issue of development on mobile devices. Mobile development has its specifics - lack of resources, unstable internet connection, short application life cycle. The course introduces the differences from desktop development and teaches best practices of mobile programming. Primarily, Kotlin language is used but just knowledge of Java is required to enter the course.
• Learning outcomes: At the end of the course the student will understand selected chapters of design and implementation of mobile applications and will be able to create a mobile application at a more advanced level, which can be published, ie. exhibit for sale and distribution. The student will understand the principles of its development cycle so that the application meets the requirements of the design patterns used.
• Syllabus: Introduction to Android and differences in the use of Android SDK versus Java SDK
  Working with the Activity and Fragment building elements
  Styles and Themes
  ViewModel
  Threads and coroutines
  Lists
  Gradle and build the project
  Working with API
  Working with database
  Application publishing

PV257 Graphic Design and Multimedia Project

k 0/2 2 kr., podzim

• MgA. Helena Lukášová, ArtD. - MgA. Jana Malíková - Mgr. Lukáš Pevný - Mgr. Kristína Zákopčanová
• Prerequisities: ( PV066 || PV078 || PV084 ) && SOUHLAS
  A precondition for this course is the artistic approach and the knowledge of the principles of graphic design, typography, and type design. Adobe CS6 software skills are expected.
• Goals: The focus of the course is to develop students' skills and ability to work on the professional level. Presented students' proposals of the graphic design will respect client's requirements and deadlines. In this course, teamwork will be encouraged which can lead to the innovative solutions combining strategies of graphic design, typography, and type design with other areas such as animation, video, 3D modeling, information graphics, visualization, photography, DTP (desktop publishing), product and package design, exhibition design, etc. In the course, students will be confronted with external experts and lecturers with the technical and artistic background also. While working on specific tasks students will utilize knowledge and experience previously acquired in prerequisite courses. This course introduces the workflow of a graphic designer expected on the professional level. The goal is to offer to students an opportunity to gain the experience while communicating with clients, presenting the work, working in teams, seeking innovative solutions.
• Learning outcomes: At the end of this course, students will create their own portfolio.
• Syllabus: Creative presentations (portfolio), a creation of a 3D font, participation in internal and external graphics and multimedia competitions, curatorship of exhibitions etc.

PV257 Graphic Design and Multimedia Project

z 0/2 2 kr., jaro

• MgA. Jana Malíková - Mgr. Lukáš Pevný - MgA. Kateřina Spáčilová
• Prerequisities: PV083 && PV067 && PV085
  A precondition for this course is the artistic approach and the knowledge of the principles of graphic design, typography, and type design. Adobe CS6 software skills are expected.
• Goals: The focus of the course is to develop students' skills and ability to work on the professional level. Presented students' proposals of the graphic design will respect client's requirements and deadlines. In this course, teamwork will be encouraged which can lead to the innovative solutions combining strategies of graphic design, typography, and type design with other areas such as animation, video, 3D modeling, information graphics, visualization, photography, DTP (desktop publishing), product and package design, exhibition design, etc. In the course, students will be confronted with external experts and lecturers with the technical and artistic background also. While working on specific tasks students will utilize knowledge and experience previously acquired in prerequisite courses. This course introduces the workflow of a graphic designer expected on the professional level. The goal is to offer to students an opportunity to gain the experience while communicating with clients, presenting the work, working in teams, seeking innovative solutions.
• Learning outcomes: At the end of this course, students will create their own portfolio.
• Syllabus: Creative presentations (portfolio), a creation of a 3D font, participation in internal and external graphics and multimedia competitions, curatorship of exhibitions etc.

PV258 Software Requirements Engineering

zk 2/ 2 kr., jaro

• Bruno Rossi, PhD - doc. RNDr. Tomáš Pitner, Ph.D.
• Prerequisities: No prerequisites are compulsory. The students are expected to have an understanding of software development models and different UML diagram types (as taught in the PB007 Software Engineering course). The course is taught entirely in the English language.
• Goals: Objectives of the course are to:
  - provide an overview of different Software Requirements types (functional vs non-functional (quality), constraints, business requirements, business rules, user and system requirements);
  - explain the Software Requirements Process (ISO/IEC/IEEE 29148 Standard for Requirements Engineering) also in agile contexts;
  - provide the instruments for the definition of user requirements;
  - describe different software requirements elicitation modalities;
  - provide approaches for requirements analysis and verification & validation;
  - provide approaches to manage requirements prioritization;
  - provide approaches for software requirements effort estimation;
  - describe the software architecture and the relevance in the context of software requirements.
  - describe how to decompose system models: abstraction, & different system views for the definition of the software architecture from the requirements;
  - describe how to model Non-Functional Requirements (NFR);
• Learning outcomes: At the end of the course students will:
  - have a clear understanding about processes, tools and techniques used in requirements engineering;
  - understand the concepts of software requirements elicitation, modelling, validation and verification;
  - be able to model software requirements rigorously according to the latest requirements engineering standards;
  - be able to conduct a prioritization process for software requirements according to different approaches;
  - be able to make a reasoned choice about the best approach for requirements modelling given the context of a project;
  - be able to proper manage requirements and their quality concerns;
  - understand the differences between different requirements modelling approaches (agile and non-agile);
  - be able to generate and maintain a software requirements specification document
• Syllabus: - Software Requirements types (functional vs non-functional (quality), constraints, business requirements, business rules, user and system requirements);
  - The Software Requirements Process (ISO/IEC/IEEE 29148 Standard for Requirements Engineering);
  - Business Requirements: vision, scope, context diagram, ecosystem maps, events lists, feature trees, the goal-design scale;
  - User Requirements: User Stories & Use cases modelling;
  - Requirements elicitation modalities: Stakeholders Analysis, design/brainstorming workshops, prototyping, pilot experiments, cost/benefit & risk analysis;
  - Requirements analysis. (C)lass (R)esponsability (C)ollaborators cards. Linking Requirements to UML Analysis Models;
  - Requirements Verification & Validation: Consistency checks, CRUD checks, Acceptance Testing;
  - Managing requirements prioritization. Analytic Hierarchy (AHP) process, Software Quality Deployment Function (SQFD), the Agile Planning Game;
  - Requirements Effort estimation & Project Velocity: Early models of effort estimation (LOCs based). Three modalities of estimation: COCOMO II, k-Nearest Neighbour, Planning Poker;
  - Emergence of the software architecture from requirements. Decomposing system models: abstraction, & different system views. The Attribute-Driven Design (ADD) Method;
  - Modelling Non-Functional Requirements (NFR): SQuaRE (Software product Quality Requirements and Evaluation) & ISO/IEC 25010;
  - From Lean to Agile Methodologies. Overview of SCRUM, XP, and other agile approaches in relation to Requirements Engineering;

PV259 Generative Design Programming

k 1/2 2 kr., podzim

• Mgr. Kristína Zákopčanová - MgA. Helena Lukášová, ArtD.
• Prerequisities: Knowledge of basic algorithms and data structures, which is taught within IB002 Algorithms and data structures I, programming knowledge corresponding to IB001 Introduction to Programming using C or similar course.
• Goals: At the end of the course, students will be able to design and implement own design solution and to present it in a comprehensive form. Namely, they will be able to compose algorithms for:
• Color palettes with different types of interpolation.
• Organizing colored regions of images according to parameters.
• Designing and implementing the rhythmic shapes, complex modules in raster, generating growing structures, animated and dynamical brushes for text rendering, combining shape with color.
• Text rendering and creative processing of vector fonts parameters. Programming and setting parameters influencing the font size and its orientation. Understanding the font visualization within a text, which is based on given parameters, working with curves and programmable mutations of fonts.
• Learning outcomes: Students passing this course will be able to: - create own visual outputs (static images, animations, interactive applications) fulfilling the generative design criteria - implement a given technique in an optimized way, with an appropriate complexity - apply the generative design principles in other fields, e.g., web design, logo design, etc.
• Syllabus: Color - color palettes and their interpolation, processing the color palette from an image, organizing colored regions of images according to parameters.
  Shape - organizing of rhythmic shapes, complex modules in raster, generating growing structures, programming brushes for text rendering.
  Fonts - parameters of the vector fonts, programming the values influencing the font size and orientation, visualization of fonts in texts, curves, font mutations.
  Randomness and noise, oscillation curves.
  Attractors, tree diagrams, dynamic data structures.

PV260 Software Quality

k 2/2 4 kr., jaro

• doc. Ing. RNDr. Barbora Bühnová, Ph.D. - Bruno Rossi, PhD
• Prerequisities: PB007 && ( PV168 || PV178 )
  
• Goals: The aim of the course is to introduce students into both theoretical and practical aspects of software quality (quality attributes, metrics, conflicts) and supportive processes (activities contributing to building software quality along the development process), and develop critical thinking that will allow them to identify code flaws and future problems early during the software development life cycle. Students will also become familiar with code refactoring and different dimensions of software testing.
• Learning outcomes: At the end of the course students will:
  understand different aspects of software quality (quality attributes, metrics, conflicts) and supportive processes (activities contributing to building software quality along the development process);
  be able to identify code flaws related to reliability, performance, scalability, maintainability and testability;
  be able to refactor existing code to improve the discussed quality attributes;
  have practical experience with different dimensions of software testing and related tools.
• Syllabus: Roadmap to software quality engineering methods.
  Software measurement and metrics, and their role in quality improvement.
  Quality in software development, Clean Code & SOLID principles.
  Bad code smells and code refactoring.
  Focus on quality attributes and conflicts between them.
  Static code analysis and code reviews.
  Requirements and test cases. From unit testing to integration testing.
  Best practices in software testing and testability. Popular testing strategies.
  Performance engineering and performance testing.
  Challenges of quality management in cloud applications.
  Continuous integration and issue tracking.
  Software quality management process.
  Quality and testing in agile.

PV262 Research methods and practice in social informatics

z 1/1 2 kr., podzim

• prof. PhDr. David Šmahel, Ph.D.
• Prerequisities: Assumes some knowledge of metodology in social sciences, such as those obtained by graduating FSS:SOC106 and/or FSS:SOC107.
• Goals: Course aims at theory and practice of research in social informatics with the goal to prepare students for their work on bachelor's thesis in the field that interconnects informatics and social science.
• Learning outcomes: After absolving this seminar: - student will be able to formulate research questions which s-he can use for bachelor thesis in social informatics - student will be able to formulate research methods which will lead to solving problems defined within research questions - student will better interconnect theoretical knowledge of methodology with practical implementation of empirical research - student will develop and describe the process of implementation of the relevant research and possible bachelor thesis
• Syllabus: 1 introduction 2 information technology as a tool for probing and society research 3 population specifics 4 ethics 5 overview of basic research methods 6 quantitative data collection 7 qualitative data collection 8 content analises 9 online research techniques 10 focus groups on-line, experiment. 11 technical aspects of online questionaires 12 presentations of students' projects 13 summary

PV263 Intercultural Management

k 1/0 1 kr., jaro

• Derek Mainwaring
• Goals: This course aims to boost students’ cross-cultural competency and ability to work in a multi-cultural context. Research has shown that multi-cultural (heterogenous) teams either perform better or worse than mono-cultural(homogenous) teams, usually worse! The key to peak performance is multi-cultural team management.
• Learning outcomes: When you have completed this course you will be able to:
  - Identify some of the factors that influence how decisions are made in cross-cultural management contexts
  - Describe key models and concepts used for comparing/contrasting cultures
  - Implement and use them appropriately in different cultural & organisational contexts
  - Assess your own cultural paradigm
  - Identify aspects of overlap between national cultures and organisational cultures
  - Evaluate the tools and concepts at your disposal to effectively manage multi-cultural teams
  - Demonstrate skills relevant to managing decisions and people in international corporations & organisations
• Syllabus: Input (12-15 hrs. of classwork):
  Managing Diversity
  - Living in a multi-cultural environment: notions of time, space & environment
  - Hofstede’s dimensions of culture
  - Other approaches to the analysis of cultures
  - “Snapshots” of cultures – USA, UK, France, Czech Rep., etc.
  
  Working in a multi-cultural context:
  - Diverse teams, virtual teams – team-building
  - Managing the multi-cultural team
  - Leadership
  - Intercultural skills set
  - Organisational culture
  
  
  Case study & project work (12hrs of group work inc. a final presentation)
  Case studies: from mini-cases to longer case/role play activities, e.g. The eOrganization exercise, Journal of Management Studies, 2008.
  Project: Managing multi-cultural (virtual) teams – the exact nature of the project(s) depends on the number, interests and availabilities of students

PV264 Advanced Programming in C++

k 2/2 3 kr., podzim

• RNDr. Nikola Beneš, Ph.D.
• Prerequisities: PB161
  
• Goals: The goal of this course is to expose students to advanced usage of the C++ programming language.
• Learning outcomes: At the end of the course the students should be able to: use the C++ language (in the newest standard) on an advanced level; use various programming techniques, notably generic, functional and parallel programming; understand the principles of memory and resource management in C++; debug, test and profile C++ programs using appropriate tools; be able to use modern C++ idioms and design patterns.
• Syllabus: Introduction to the ISO C++17 and ISO C++20 standards
  Build process; Debugging and testing
  Functional programming in C++, lambda functions, algorithms
  Move semantics: rvalue references, forwarding
  Resource management, smart pointers, the RAII idiom
  Profiling and optimizations
  Generic programming and meta-programming using templates (variadic templates, SFINAE, ...)
  Modern C++ idioms (CRTP, tags)
  Parallel programming in modern C++: threads, atomic, introduction to lock-free data structures
  Concepts
  The future of the standard library: Ranges

PV266 Game Development II

k 0/1 3 kr., jaro

• Mgr. Jiří Chmelík, Ph.D. - Mgr. Milan Doležal
• Prerequisities: PV255
  Digital game development related knowledge (in the scope of course PV255 Game Development I).
• Goals: At the end of the semester, a student will be able to:
  understand and explain a process of digital game development;
  design and implement their own digital games;
• Learning outcomes: At the end of the course a student should be able to:
  - effectively work in the small team
  - be able to work on all stages of digital game development (planning, design, assets creation, programming, testing, building and releasing)
  - design and create their own digital game
• Syllabus: pre-production phase - design document, playable prototype
  the first presentation of the project
  production phase - design and implementation of game logic, assets creation
  the second presentation of the project
  post-production phase - testing, debugging, profiling, releasing
  the final presentation of the project

PV267 Graphic Design for Web

k 2/0 2 kr., podzim

• MgA. Helena Lukášová, ArtD. - MgA. Jana Malíková
• Prerequisities: Basic knowledge of graphic design principles and building the web structure.
• Goals: The ability to create a functional prototype of web-based on student's original design.
• Learning outcomes: A student will have the theoretical knowledge and practical experiences regarding web design structure and user interface.
• Syllabus: 1. Introduction to user interface designs, methods of designing
  2. Analysis of the task, user evaluation and research, data modeling A
  3. Definition of goals, definition of requirements of software functions
  4. Conceptual design of user interface
  5. Final graphic design
  6. Making of the prototype
  7. Evaluation of the design, testing the prototype

PV268 Digital Design

k 2/0 2 kr., podzim

• MgA. Helena Lukášová, ArtD.
• Prerequisities: A precondition for this course is the artistic approach and the respect for the character of typography and graphic design, including the manual execution of the projects.
• Goals: Bachelor and Master degree course is a continuation of PV083 Graphic Design II and PV067 Typography II. The aim of this course is to create interactive publications for mobile devices using visual communication, animation, illustration, and information graphics. In the process, students will obtain knowledge of e-publishing in Adobe Indesign CS6 and animations using HTML5. Students are expected to a pro-active approach to solving new technological procedures.
• Learning outcomes: A student will understand the subject of the graphic design and typography, will be able to design and implement a motion graphics and will be able to relate the motion graphics with static elements and dynamic picture through e-publishing.
• Syllabus: Magazine layout.
  Typographic Style and Unifying Elements
  The target group for Media
  Model of a printed magazine.
  Digital interactive magazine for Ipads or SmartPhones.

PV269 Advanced methods in bioinformatics

zk 2/0 3 kr., jaro

• Ing. Matej Lexa, Ph.D.
• Prerequisities: The student is expected to have basic knowlege in bioinformatics. They must have passed IV108. Previous study of IV107, PA052 a PB050 is recommended.
• Goals: To acquire practical skills in bioinformatics beyond the scope of bachelor courses, extending theoretical topics from IV108.
• Learning outcomes: The student will be able to choose appropriate computational methods for a given problem; obtain and prepare relevant data; carry out necessary computation using their own or publicly available programs.
• Syllabus: Genomic sequences
  - Advanced techniques for NGS data
  - Sequence motif detection and genome annotation
  - Advanced work with genome browsers
  Proteins
  - Hidden Markov models (HMM)
  - Protein structure analysis

PV270 Biocomputing

zk 2/0 2 kr., jaro

• doc. RNDr. David Šafránek, Ph.D.
• Goals: The course presents an overview of natural computing, with an emphasis on biomolecular (DNA) computing, cellular computing and molecular programming.
• Learning outcomes: After following the course, student will be able to:
  - to understand basic notions of biocomputing;
  - to identify fundamental bio-operations performed on the biological matter;
  - to associate suitable formalisms with a concrete computation platform.
• Syllabus: Introduction to Biocomputing
  Notions of Molecular Biology and Biotechnology
  Bio-inspired systems
  
  Physical Mapping
  Encoding information in DNA
  Bio-operations
  DNA models of computation, DNA nanocomputation by self-assembly
  Cellular computing
  Membrane computing
  Molecular programming

PV271 Risk Management in IT

zk 2/1 3 kr., podzim

• Stanislav Masák, M.Sc. - doc. RNDr. Tomáš Pitner, Ph.D.
• Goals: The aim of the course is to provide a basic overview of the various types of risks that affect the IT area, as well as the ways of their management.
• Learning outcomes: At the end of the course students should be able:
  - to identify the risks they may encounter during their IT career;
  - to analyze and measure the identified risk using appropriately chosen method;
  - to apply risk management techniques.
• Syllabus: Introduction to Risk management in IT
  Definition of risk and its types
  Risk management
  Risk measurement
  Financial analysis in risk management decision making
  Risk management tools (Value at risk analysis)
  Techniques of risk management
  Insurance and risk
  Information system security risk
  Enterprise risk management
  Enterprise risk management in projects
  Risk management in practice

PV272 3D Modelling

k 0/2 3 kr., jaro

• Mgr. Jiří Chmelík, Ph.D.
• Prerequisities: Knowledge of computer graphics theory basics is expected, e. g. in the scope of course PB009 Principles of Computer Graphics. Students should know terms such as b-spline, polygon mesh, texture mapping or global illumination.
• Goals: The main goal of the course is to give students practical skills and experience in the area of 3D modelling. Topics such as polygonal modelling, applying textures and lighting or basics of animation will be covered during practically oriented seminars. Emphasis will be placed on individual work of students. The course complements the theoretical lectures of PB009 Principles of Computer Graphics.
• Learning outcomes: Student will be able to:
  - create the 3D model of objects from given assignment (photo reference, blueprints, etc.);
  - apply textures, materials and lighting to create the realistic 3D scene;
  - create a simple animation of created model;
  - postprocess a given model for further usage (e. g. 3D print, digital games, VR);
  - apply learned processes in various 3D modelling software tools;
• Syllabus: Basic terms and tools of Cinema4D software
  Graphical primitives, constructive solid geometry
  Parametric curves and surfaces
  Polygonal modelling
  Textures, materials and lighting
  Animations
  Sculpting
  Composition, rendering
  Postprocessing

PV273 Seminar of Sitola Laboratory

z 0/2 2 kr., podzim

• doc. Mgr. Hana Rudová, Ph.D. - doc. RNDr. Eva Hladká, Ph.D. - prof. RNDr. Luděk Matyska, CSc.
• Goals: The goal of the seminar is to get acquainted with the latest trends in the research field relevant to the work of Sitola laboratory. The research laboratory is specializing in high performance computing, interdisciplinary research in chemistry and biology, multimedia and networking, planning and scheduling.
• Learning outcomes: Experience with a presentation of recent scientific results.
• Syllabus: The content of the seminar is made up of selected topic presentations.

PV273 Seminar of Sitola Laboratory

z 0/2 2 kr., jaro

• doc. Mgr. Hana Rudová, Ph.D. - doc. RNDr. Eva Hladká, Ph.D. - prof. RNDr. Luděk Matyska, CSc.
• Goals: The goal of the seminar is to get acquainted with the latest trends in the research field relevant to the work of Sitola laboratory. The research laboratory is specializing in high performance computing, interdisciplinary research in chemistry and biology, multimedia and networking, planning and scheduling.
• Learning outcomes: Experience with a presentation of recent scientific results.
• Syllabus: The content of the seminar is made up of selected topic presentations.

PV274 Data Quality Management Seminar

zk 0/2 1 kr., podzim

• doc. Mouzhi Ge, Ph.D.
• Prerequisities: Database Design and Data Modelling
  Basic statistics or software experience like using SAS, R, SPSS is preferred
• Goals: (This course requires very interactive discussion, it is designed for the second-year or final-year students) This course is designed to let students learn practical and scientific knowledge of data quality management. The main objective is to exploit the techniques used in data quality management and data integration. The course will also provide theoretical knowledge of data quality management and the real-world system implementation guidelines to students such as Talend DI and DQ. The students will learn and discuss the applications according to the case studies in ETL with Talend software.
• Learning outcomes: After completing the course, a student will be able to:
  - understand the classic research methods in the data quality management;
  - apply the data quality management solutions in practice;
  - understand the data quality dimensions and their measurement;
  - analyze current scientific knowledge in the field of data quality management;
  - conduct the data quality measurement;
  - design real-world data quality management scenarios;
  - identify and describe data models;
  - apply management principles to big data;
  - understand the data integration and ETL concepts ;
  - implement the real-world data quality measurement solution;
  - understand the theoretical knowledge of data quality management;
• Syllabus: Data quality management
  Data quality dimensions
  Big Data quality
  Master Data Management
  Talend Software: DI and DQ
  Data quality assessment
  ETL and Data Integration
  Data quality costs
  Data cleansing
  Data quality management strategy
  Data analytics
  A/B test in practice
  Delone and Mclean IS model
  Optimizing Information Value
  Information Lifecycle Concepts
  Data modelling in different domains
  Data quality and smart city

PV275 Introduction to Quantum Computer Programming

zk 2/2 3 kr., podzim

• doc. RNDr. Jan Bouda, Ph.D. - doc. Mgr. Mário Ziman, Ph.D.
• Prerequisities: ( MB141 || MB151 || MB101 || MB201 ) && IB111
  Basic knowledge of linear algebra, probability theory, programming in Python
• Goals: This is an introductory course to quantum information. The main goal is to provide students with basic idea what are the expected applications of quantum information processing, how quantum computing and communication works, and give them practical experience how to program quantum computer. All programming will be performed using Python language and IBM Quiskit library.
  
  As a part of the course we want students to become comfortable with basic mathematics necessary for quantum information processing. While you already know almost all necessary mathematics from prerequisite courses, there is a big difference between knowing something and being able to use it an intuitive and efficient way.
  
  The course is designed in the way that it introduces in a parallel way basic quantum information applications, necessary mathematical concepts and teaches how to implement these applications on quantum computers. As an example, on second lecture you will learn about BB84 quantum key distribution. On this concept we will explain what quantum state is, what is a quantum measurement, and we will learn how to implement BB84 using the Quiskit Python library. In this way we avoid boring monothematical blocks of mathematics.
  
  This course will be in future followed by two advanced courses. The second course will introduce all necessary concepts of quantum information processing – necessary concepts from mathematics, physics and informatics, so that student will have all theoretical knowledge necessary to work with quantum information processing. The third course will explain the applications of quantum information processing in full scale – communication, algorithms, cryptography, NP-approximation, machine learning, simulation of physical and chemical systems.

• Learning outcomes: After completing the course, a student
• will be able to implement simple quantum programs using the IBM Quiskit library
• will know basic applications of quantum information processing
• and will be able to program them using the IBM Quiskit library
• will be able to perform basic mathematical calculations necessary for quantum information processing applications
• Syllabus: More detailed syllabus is provided in the study materials, namely in the Interactive syllabi.

• Quantum information processing, tools and applications.
• Existing quantum technologies (IBM, Toshiba, Google, Microsoft, D-wawe, Qusoft, idQuantique), Chinese backbone quantum network, quantum satellites.
• BB84 quantum key distribution, Bell inequalities, entanglement-based key distribution.
• Quantum teleportation.
• Quantum encryption.
• Quantum bit commitment and coin flipping.
• Grover’s search.
• Quantum processors, universal sets of quantum gates, approximation.

PV276 Seminar on Simulation of Cyber Attacks

k 0/2 3 kr., podzim

• RNDr. Jan Vykopal, Ph.D. - Mgr. Jakub Bartolomej Košuth
• Prerequisities: ( PB156 && PV004 ) || SOUHLAS
  
• Goals: The course enables students to learn cybersecurity topics practically. Students will learn standard attack techniques as well as detection and prevention methods in a simulated environment of KYPO cyber range. These skills will be exercised in the preparation of a cybersecurity game, which the student teams will present at a public event.
• Learning outcomes: At the end of the course, students will be able to:
      • understand current cybersecurity threats,
      • conduct penetration testing using suitable tools,
      • apply suitable methods of detection and prevention of vulnerabilities,
      • create a virtual environment with selected vulnerabilities of computer systems and applications,
      • create a cybersecurity game in KYPO cyber range.
• Syllabus: The course has two parts.
  The first part introduces selected topics of cybersecurity, including attack types and techniques, network traffic analysis, forensic analysis, and prevention methods.
  In the second part, teams of students prepare cybersecurity games at KYPO cyber range.
  The created games are publicly presented at the end of the semester.

PV276 Seminar on Simulation of Cyber Attacks

k 0/2 3 kr., jaro

• RNDr. Jan Vykopal, Ph.D. - Mgr. Jakub Bartolomej Košuth
• Prerequisities: ( PB156 && PV004 ) || SOUHLAS
  
• Goals: The course enables students to learn cybersecurity topics practically. Students will learn standard attack techniques as well as detection and prevention methods in a simulated environment of KYPO cyber range. These skills will be exercised in the preparation of a cybersecurity game, which the student teams will present at a public event.
• Learning outcomes: At the end of the course, students will be able to:
      • understand current cybersecurity threats,
      • conduct penetration testing using suitable tools,
      • apply suitable methods of detection and prevention of vulnerabilities,
      • create a virtual environment with selected vulnerabilities of computer systems and applications,
      • create a cybersecurity game in KYPO cyber range.
• Syllabus: The course has two parts.
  The first part introduces selected topics of cybersecurity, including attack types and techniques, network traffic analysis, forensic analysis, and prevention methods.
  In the second part, teams of students prepare cybersecurity games at KYPO cyber range.
  The created games are publicly presented at the end of the semester.

PV277 Programming Applications for Social Robots

k 0/1 1 kr., podzim

• doc. RNDr. Aleš Horák, Ph.D. - RNDr. Adam Rambousek, Ph.D.
• Prerequisities: Basic knowledge of programming in Python.
• Goals: The purpose of the seminar is to give a deeper insight into the possibilities of chatbots and robots communicating with people, and applications in the field of social robots. The course work includes an individual project elaboration and development of an application for the Pepper robot.
• Learning outcomes: At the end of the course, students should be able to: describe principles and algorithms used for human-computer interaction; independently analyze and design an application in this area; choose a suitable implementation procedure and develop an application for the selected robot model.
• Syllabus: Existing approaches and algorithms for human-computer communication; Chatbots and dialog systems; Speech recognition and synthesis; Social robots - specific applications from different areas of interaction; HW and SW equipment of selected robot models; Control methods and interface description for programming Pepper robot; Elaboration of individual project

PV277 Programming Applications for Social Robots

k 0/1 1 kr., jaro

• doc. RNDr. Aleš Horák, Ph.D. - RNDr. Adam Rambousek, Ph.D.
• Prerequisities: Basic knowledge of programming in Python.
• Goals: The purpose of the seminar is to give a deeper insight into the possibilities of chatbots and robots communicating with people, and applications in the field of social robots. The course work includes an individual project elaboration and development of an application for the Pepper robot.
• Learning outcomes: At the end of the course, students should be able to: describe principles and algorithms used for human-computer interaction; independently analyze and design an application in this area; choose a suitable implementation procedure and develop an application for the selected robot model.
• Syllabus: Existing approaches and algorithms for human-computer communication; Chatbots and dialog systems; Speech recognition and synthesis; Social robots - specific applications from different areas of interaction; HW and SW equipment of selected robot models; Control methods and interface description for programming Pepper robot; Elaboration of individual project

UA104 Didactics for Informatics I

k 0/2 2 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Prerequisities: Knowledge of general didactics or pedagogy.
• Goals: Each student will be assigned topics from the domain of computer science. The student makes methodical preparation of the given topics and presents them in a form of high school lesson. The presentation is then evaluated with regard to its fundamental and didactic correctness at the end of the presentation.
• Learning outcomes: At the end of this course, students should:
  know basic methodical techniques for computer science teaching at high schools;
  be able to present given topics (in a form of high school lesson).
• Syllabus: Methodical proccessing of the particular chapters of the basic courses (architecture of computers, design of algorithms and programming, operating systems, computer networks and Internet).
  A papers within 30 - 45 minutes. Discussion and evaluation of the particular papers.

UA105 Didactics for Informatics II

zk 1/2 3 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D.
• Prerequisities: UA104
  Passing the course UA104 Didactics for Informatics I.
• Goals: In the course Didactics of Informatics II the students are introduced to methodical recommendations for computer science teaching at high schools and basic schools. The students also obtain information about study programs dealing with computer science at various types of high schools. They learn to make their own teaching plans, that are based on a given study program.
• Learning outcomes: At the end of this course, students should:
  know methodical recommendations for computer science teaching at high schools and basic schools;
  be acquainted with study programs dealing with computer science at various types of high schools;
  be able to make their own teaching plans, that are based on a given study program;
  be able to present given topics (in a form of high school lesson).
• Syllabus: Pedagogical and didactical concepts of computer science education.
  Users, algorithmic and project approach.
  Study programs of informatics at basic and high schools.
  Administration of computer schoolrooms.
  Teaching tools, educational software, multi-licenses.
  Methodical processing of the particular chapters of the basic courses (architecture of computers, design of algorithms and programming, operating systems, computer networks and Internet).
  A papers within 30 - 45 minutes. Discussion and evaluation of the particular papers.

UA442 Exercises in Practical Education I

z 0/0 4 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The main objective of this course is to expose students to their future professional activities so as they can test their pedagogical skills.
• Learning outcomes: At the end of this course, students should:
  be able to present given topics (in a form of primary school lesson).
• Syllabus: Individual teaching practice at primary school under the supervision of an experienced teacher. The teaching practice includes 15 lessons of sittings-in on a class, 15 lessons of presentations on class, and 15 hour work devoted to school operation.

UA542 Exercises in Practical Education II

z 0/0 4 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The main objective of this course is to expose students to their future professional activities so as they can test their pedagogical skills.
• Learning outcomes: At the end of this course, students should:
  be able to present given topics (in a form of secondary school lesson).
• Syllabus: Individual teaching practice at secondary school under the supervision of an experienced teacher. The teaching practice includes 15 lessons of sittings-in on a class, 15 lessons of presentations on class, and 15 hour work devoted to school operation.

UA642 Exercises in Practical Education III

z 0/0 2 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The main objective of this course is to expose students to their future professional activities (at a secondary school or at a university) so as they can test their pedagogical skills.
• Learning outcomes: At the end of this course, students should:
  be able to present given topics (in a form of secondary school lesson or in a form of university class exercise).
• Syllabus: Individual teaching practice at secondary school under the supervision of an experienced teacher (20 lessons of presentations on class) or supervising of university class exercise for some of the courses focused on programming (one semester).

UA742 Exercises in Practical Education IV

z 0/0 4 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The main objective of this course is compensate for the lack of practical teaching in the other field for students that follow one-approval teacher's study plan.
• Learning outcomes: At the end of this course, students should:
  be able to present and explain given IT topic in a standalone-lead lecture to students whose education in informatics reflects the usual secondary school IT curriccula.
• Syllabus: Individual teaching practice at secondary school under the supervision of an experienced teacher (40 lessons of presentations on class) or supervising of at least two university class exercise for some of the courses focused on programming (one semester).

UA842 Exercises in Practical Education V

z 0/0 6 kr., jaro

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The main objective of this course is compensate for the lack of practical teaching in the other field for students that follow one-approval teacher's study plan.
• Learning outcomes: At the end of this course, students should:
  be able to present and explain given IT topic in a standalone-lead lecture to students whose education in informatics reflects the usual secondary school IT curriccula.
• Syllabus: Individual teaching practice at secondary school under the supervision of an experienced teacher (40 lessons of presentations on class) or supervising of at least two university class exercises for some of the courses focused on programming (one semester).

UB001 Assesment of teaching in Informatics

k 0/2 3 kr., podzim

• RNDr. Jaroslav Pelikán, Ph.D.
• Goals: The aim of this course is to attend lectures of a chosen informatics course (during one semester) and from a pedagogical-didactic point of view observe the teaching process.
• Learning outcomes: At the end of this course, students should:
  be able to review a teaching process from a pedagogical-didactic point of view.
• Syllabus: Regular attendance of a selected informatics course lectures. Observation of teaching process. Elaboration of report (3 to 5 pages) evaluating (from a pedagogical-didactic point of view) presented semester course.

VB000 Elements of Style

k 1/1 2 kr., podzim

• prof. PhDr. Karel Pala, CSc. - RNDr. Zuzana Nevěřilová, Ph.D. - PhDr. Petr Peňáz - Mgr. Marie Stará
• Prerequisities: NOW ( SBAPR )
  Ability to communicate and write texts on the high school level requirements. Students are supposed to already have their bachelor's thesis topics selected.
• Goals: At the end of this course students should be able: to master the principles of the positive communication, knowledge of communication barriers and the ways of their overcoming; to apply rules for writing technical texts in theory and practice; to acquire the basic skills for writing technical texts (introduction to Bachelor thesis and the state-of-the-art chapter); to recognize and correct spelling and grammatical errors in the technical texts; to possess a basic knowledge about orthography systems and the rules of language correctness; to prepare oral presentation about the given topic; to learn the basic rules of the correct argumentation; To sum up: students should be able to communicate and write both technical and normal texts with correct spelling and composition;
• Learning outcomes: The students will:
  determine the academic style main characteristics (formal, precise, structured, using hedging);
  plan the written part of their bachelor thesis;
  select appropriate academic resources for their domain;
  summarise current state-of-the-art for their domain;
  formulate the aim, methods, and results of their bachelor thesis;
  cite appropriately academic resources;
  write abstract
• Syllabus: Communication maxims, basic principles of the positive communication.
  Communication barriers and the ways of their overcomning.
  Communication skills, practical writing
  Language and communication, various registers and styles.
  Language correctness, spelling, orthography, language support software.
  Colloquial and Common Czech, dialects, slangs.
  Writing technical and research documents, their composition, vertical and horizontal structuring, lexical features, terms, terminology.
  Oral and written presentations: talks, lectures, articles, posters etc.

VB000 Elements of Style

k 1/1 2 kr., jaro

• prof. PhDr. Karel Pala, CSc. - RNDr. Zuzana Nevěřilová, Ph.D. - PhDr. Petr Peňáz - Mgr. Marie Stará
• Prerequisities: NOW ( SBAPR )
  Ability to communicate and write texts on the high school level requirements. Students are supposed to already have their bachelor's thesis topics selected.
• Goals: At the end of this course students should be able: to master the principles of the positive communication, knowledge of communication barriers and the ways of their overcoming; to apply rules for writing technical texts in theory and practice; to acquire the basic skills for writing technical texts (introduction to Bachelor thesis and the state-of-the-art chapter); to recognize and correct spelling and grammatical errors in the technical texts; to possess a basic knowledge about orthography systems and the rules of language correctness; to prepare oral presentation about the given topic; to learn the basic rules of the correct argumentation; To sum up: students should be able to communicate and write both technical and normal texts with correct spelling and composition;
• Learning outcomes: The students will:
  determine the academic style main characteristics (formal, precise, structured, using hedging);
  plan the written part of their bachelor thesis;
  select appropriate academic resources for their domain;
  summarise current state-of-the-art for their domain;
  formulate the aim, methods, and results of their bachelor thesis;
  cite appropriately academic resources;
  write abstract
• Syllabus: Communication maxims, basic principles of the positive communication.
  Communication barriers and the ways of their overcomning.
  Communication skills, practical writing
  Language and communication, various registers and styles.
  Language correctness, spelling, orthography, language support software.
  Colloquial and Common Czech, dialects, slangs.
  Writing technical and research documents, their composition, vertical and horizontal structuring, lexical features, terms, terminology.
  Oral and written presentations: talks, lectures, articles, posters etc.

VB001 English Exam

zk 0/0 1 kr., podzim

• Mgr. Lucie Procházková - Mgr. Eva Rudolfová - Mgr. Marcela Sekanina Vavřinová - Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: Enrolment prerequisite for this exam is the completion of the VB035 and VB036 courses or the knowledge of the grammar, vocabulary, and phrases taught at these courses.
• Goals: Students should be able to: understand specialized articles; use the language fluently; talk about a wide range of IT related topics; provide relevant explanations and arguments; give clear descriptions and presentations; answer questions and interact fluently and spontaneously.
• Learning outcomes: Students will be able to - communicate in English about their field of study; - write formal emails (requests, applications, complaints etc.); - understand spoken and written English on general and general academic level + their field of expertise; - present their ideas/ findings efficiently; - interact efficiently and politely with others - negotiate, debate, cooperate and solve problems constructively; - think critically and argue in an informed way; - plan and reflect, provide and receive feedback and act upon it.
• Syllabus: Grammar, vocabulary and phrases at B2 level; these include: - past, present, and future tenses - conditional sentences - modal verbs - passives - wish clauses - reported speech - relative clauses, participles - adverbs and prepositions - gerund vs. infinitive - question tags - comparisons, quantifiers - articles, determiners, countable/uncountable nouns
  English for Specific Purposes, English for Academic Purposes
  Listening, reading, writing and speaking skills

VB001 English Exam

zk 0/0 1 kr., jaro

• Mgr. Lucie Procházková - Mgr. Eva Rudolfová - Mgr. Marcela Sekanina Vavřinová - Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: Enrolment prerequisite for this exam is the completion of the VB035 and VB036 courses or the knowledge of the grammar, vocabulary, and phrases taught at these courses.
• Goals: Students should be able to: understand specialized articles; use the language fluently; talk about a wide range of IT related topics; provide relevant explanations and arguments; give clear descriptions and presentations; answer questions and interact fluently and spontaneously.
• Learning outcomes: Students will be able to - communicate in English about their field of study; - write formal emails (requests, applications, complaints etc.); - understand spoken and written English on general and general academic level + their field of expertise; - present their ideas/ findings efficiently; - interact efficiently and politely with others - negotiate, debate, cooperate and solve problems constructively; - think critically and argue in an informed way; - plan and reflect, provide and receive feedback and act upon it.
• Syllabus: Grammar, vocabulary and phrases at B2 level; these include: - past, present, and future tenses - conditional sentences - modal verbs - passives - wish clauses - reported speech - relative clauses, participles - adverbs and prepositions - gerund vs. infinitive - question tags - comparisons, quantifiers - articles, determiners, countable/uncountable nouns
  English for Specific Purposes, English for Academic Purposes
  Listening, reading, writing and speaking skills

VB003 Economic Style of Thinking I

z 2/0 1 kr., podzim

• Ing. Jitka Dušková, Ph.D.
• Goals: Introduction to economics. The economy and the three fundamental questions. The price system, supply and demand analysis. The determination of demand elasticity. The theory of utility. The income effect and the substitution effect. Market equilibrium. Supply and costs. The firm's supply curves. General equilibrium and the efficiency of perfect competition. Imperfect competition - Monopoly, Oligopoly and monopolistic competition. The price of labor. Interest, rent and profits.
• Learning outcomes: Student will get very basic terminology and knowledge of economics.
• Syllabus: Introduction to economics.
  The economy and the three fundamental questions.
  The price system, supply and demand analysis.
  The determination of demand elasticity.
  The theory of utility.
  The income effect and the substitution effect.
  Market equilibrium.
  Supply and costs.
  The firm's supply curves.
  General equilibrium and the efficiency of perfect competition.
  Imperfect competition - Monopoly, Oligopoly and monopolistic competition.
  The price of labor.
  Interest, rent and profits.

VB004 Economic Style of Thinking II

k 2/0 2 kr., jaro

• Ing. Jitka Dušková, Ph.D.
• Prerequisities: VB003
  
• Goals: The introductory part deals with measuring national economy performance, problems connected with economic equilibrium, and causes and manifestations of cyclical oscillations. The following part of the course explains the nature of money, structure of the banking system and basic conditions of inflation. It explains the economic function of the state, targets and instruments of economic policy, basic context of monetary policy, fiscal policy, external business and incomes policy.
• Learning outcomes: Students undesrtand basic macro-economic terms and relations.
• Syllabus: Measuring macroeconomics activity.
  Explaining business cycles and growth.
  Aggregate demand - aggregate supply model.
  A simple model of the macroeconomy: the multiplier model.
  Money and the financial system.
  Determination of the interest rate.
  Unemployment and inflation.
  Monetary and fiscal policy.
  International trade and the theory of comparative advantage.
  Open economy macroeconomics: exchange rates, the balance of payments.

VB005 Panorama of Physics I

z 2/0 1 kr., podzim

• prof. RNDr. Josef Humlíček, CSc.
• Goals: At the end of this course students should be able to understand concepts of classical and modern physics, and to work with the basic knowledge in the field of mechanics, electromagnetism, thermodynamics and structure of matter.
• Learning outcomes: At the end of this course students should be able to understand concepts of classical and modern physics, and to work with the basic knowledge in the field of mechanics, electromagnetism, thermodynamics and structure of matter.
• Syllabus: A brief history of physics. Cornerstones of classical and modern physics. Understanding and predicting.
  Universe and microworld. Space and time, reference frames.
  Newton laws of motion. Gravitation. The movement of celestial bodies and satellites.
  Mathematical form of physical theories. Principle of least action, Lagrange and Hamilton equations.
  Symmetry. Conservation laws.
  A selection of solvable problems of classical mechanics.
  Electricity and magnetism. Electromagnetic field. Maxwell theory.
  Theory of relativity. Lorentz transform. Relativistic effects.
  Microscopic structure of matter. Dimensions in microworld. Microscopic description of macroobjects.
  Atoms, isotopes, periodic table. Scanning microscopes.
  Bonding. Molecules, condensed matter; typical properties. Unexpected stable structures (fullerenes, nanotubes).
  Probabilistic description of gases. Energy and temperature. Remarkable behavior at low temperatures.

VB006 Panorama of Physics II

k 2/0 2 kr., jaro

• prof. RNDr. Josef Humlíček, CSc.
• Prerequisities: VB005
  
• Goals: At the end of this course students should be able to understand concepts of classical and modern physics, and to work with the basic knowledge in the field of quantum mechanics, statistical physics, condensed mater physics, nuclear physics, and astrophysics.
• Learning outcomes: At the end of this course students should be able to understand concepts of classical and modern physics, and to work with the basic knowledge in the field of quantum mechanics, statistical physics, condensed mater physics, nuclear physics, and astrophysics.
• Syllabus: Manipulating gas and free electrons. Work and heat. Irreversibility.
  Maxwell demon. Entropy. Probabilistic view of irreversibility.
  Thermal radiation, classical and quantum description. Cosmic microwave background. Cosmic sailing.
  Basics of quantum theory. Waves as particles, particles as waves. Superposition of states, probability amplitudes. Measurement. Einstein against Bohr.
  Schrodinger equation. Structure of atoms. Indistinguishable particles. Back to the periodic table.
  Condensed matter. Si and GaAs. Microelectronic structures.
  Thermodynamics of computation. Quantum computers.
  Low=dimensional structures. Photonics.
  Atomic nucleus. Nuclear forces and models of nuclei. Radioactivity. Nuclear reactions.
  Elementary particles. Quantum electrodynamics. Particles and antiparticles.
  Astrophysics. Structure and evolution of stars. Cosmology.
  Great problems of contemporary physics.

VB007 Philosophy of Science I

z 2/0 2 kr., podzim

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: The course presupposes some interest in general problems of science (as knowledge of the world and life in it). It is recommended to follow by Philosophy of Science II. We should at last understand this intellectula evolution as a breathtaking "exponential" of this time.(In the preceding years, the "talk-show" method has been applied for the introduction of new contemporaneous knowledge as being systematically integrated.)
• Goals: Science is a specific activity of man. It covers induction, deduction, category of quantity, causality, criteria of verification since the beginning of the 17th century till the start of the 20th century, to enable an understanding of the exponential development of science beginning in the 20th century.
• Learning outcomes: The student will thereby have a better understanding and interpretation of the exponential develompent of science in the 20th and 21st centuries. Science as a sspecific institution started to slowly exist beginning in the 16th and 17th centuries; which the student will be able to compare with our contemporaneity.
• Syllabus: Introduction: "Time boundaries" in general.
  Birth of science as a modern phenomenon, its problems, methods and criteria. Presuppositions to a "paradigmatically" new perspective to the world and human tradition.
  The geocentric problem as a confrontation of sensual absurdity with the necessity of adequately describing it and thus enabling its prediction. (From scholastic solutions to a definite break with the Aristotelian tradition.)
  From sublunar steps to the first big jump into the supralunar world.
  What, and how, is reality? Is its adequate clue empirism, or rationalism?
  Encyclopedia as a product of Enlightenment.
  Hume's skepsis over causality. Laws and probability.
  Physiocratism as a projection of an "harmonic order", at the same time as a first model application in economics.
  The positivist experiment in trying to change the world by the force of ideas. The initial variants of physicalism.
  Problem of humanities at the end of 19-th century. (Is it possible to apply the natural-science criteria in humanities?)
  "Rationally" fighting "fiction", or does the invisible exist?
  Einstein's and Planck's shade.
  An awkward look back and forward on the threshold of the third millennium.
  The beginning of the philosophy of science.

VB008 Philosophy of Science II

z 2/0 2 kr., jaro

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: VB007
  It is not necessary to pass the preceding course ("Philosophy of science I") to participate but it may be helpful.
• Goals: This part of lectures substantially considers the problem of evolution and the dramatic development of science in the 20-th and at the beginning of this century, including physics, biotechnologies and questions of cosmology. The contemporary situation in the natural sciences has been followed regularly, including novelties.
• Learning outcomes: The student will not only have a firmer knowledge of science as developing exponentially, but moreover will be able to quote some surprising examples of this development form various domains.
• Syllabus: Evolutionary theory in the history of human thinking. Darwin. Neodarwinism. From DNA to biotechnologies.
  The way to the deductive-nomological and inductive-statistical modellings.
  Individualism, holism and the problems of being objective in social sciences.
  Inductivism as a problem. Conventionalism.
  New paradigms on the horizon? (From Einstein to Kuhn?)
  The "Why?"-question. The logic of questions. - Description as against explanation. - The pragmatics of explanation.
  Some general questions of the theory of science from the beginning of the Eighties. Some views concerning reductionism.
  Probabilistic causality. Explanation by means of laws?
  Artificial intelligence.
  Sociobiology.
  Theory vs. laws? The importance of deduction. Is the structure of the world not causal, all the same? - The "theory of all"?

VB010 Philosophy of Language and Its Problems I

z 2/0 2 kr., podzim

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: The course presupposes an interest in questions connected with language/speech, preceding logic or following from its analysis, and being often interdisciplinary. We inherited "our" language so that it, in no small measure, exerts influence upon our perception and interpretation of reality.
• Goals: A logical and linguistic analysis of language, and both as a partial presupposition of a general ("philosophical") interest in language as a special human phenomenon. The relationships of language to the world and its sometimes doubtful interpretation has to be taken into account.
• Learning outcomes: The student will somehow acquire a better relationship to language. He more insistently will differ between formal and content requirements concerning its presentation.
• Syllabus: An introduction to the "philosophy of language", especially in its relation to logic and analytical philosophy.
  Is language only a misleading instrument? Is its postmodern interpretion directed?
  An aside: The expression "knowledge" and its connotations of meaning. To know What, That, How, Why. The knowledge of things and truths.
  Towards a theory of the world and language, as well as the mind, though in a preliminary way.
  A way towards a linguistic theory.
  Semiotics and semantics.
  Languages and a language.
  A sentence, a proposition, and "linguistic acts".
  The relationship of thinking towards the world, language, logic and consciousness. The "Twin Earth" thought experiment.
  Intention and convention.
  Things and properties, or also, truth and reality.
  Language and artificial intelligence. The so-called "Chinese Room Argument".

VB011 Philosophy of Language and Its Problems II

z 2/0 2 kr., jaro

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: VB010
  It is not necessary to pass course VB010 to participate in this one.
• Goals: As an introduction serves a comparison of real processes with their model forming and interpretation. Follows an exposition of two mutually incongruous conceptions, on one side Chomsky's innate dispositions, and on the other side inspirations by Foucault and Derrida. As a conclusion a broader (and modernized) introduction into the questionable truth theory has been presented.
• Learning outcomes: The student wil be able to substantiate in a concrete way by various authors the recent development of the theoretical background od language.
• Syllabus: An introduction concerning the so-called "artificial intelligence".
  Some new reflections on reductionism.
  "To represent", or about signs.
  "To speak", or a theory of verbs.
  "To classify", or a system and method.
  "To exchange", or various types of communication.
  "To deconstruct", to make a "reconstruction"?
  In between of an anthropomorphic interpretation of nature and a physiomorphic self-interpretation of man.
  Interlude: Some paradigms "in the game".
  A metaphor within the theory of knowledge, or the problem of the inforrmation value and the mechanism of picturesque speech.
  First: the performative theory of truth.
  The correspondence theory of truth.
  The coherence theory of truth.

VB023 Folk Music

z 1/1 2 kr., podzim

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: basic information about the creation, development and poetics of modern folk song genre (both Czech (60s to 80s) and foreign); offer the students of computer science counterbalance to their specialized courses and entice them into an active approach to cultural and social events. At the end of the course students should be able to understand and explain development and poetics of modern folk song genre; interpret contemporary folk songs.
• Learning outcomes: Student will be able to:
  formulate the specifics of the genre of folk music;
  characterize the poetics of the main representatives of the genre;
  analyze the given folk music both in terms of music and text;
  to clarify the influence of computer music on the genre of folk music;
  apply copyright to folk music.
• Syllabus: The origin, development and poetics of Contemporary Urban Adult Music, its current and future relations to the other kinds of music.
  Singing poets and poetry turned into music. Woody Guthrie, Pet Seeger, Bob Dylan, Joan Baez, Leonard Cohen, Joni Mitchell, Bulat Okudžava, Vladimír Vysockij, Karel Kryl, Vladimír Merta, Jaroslav Hutka, Vlastimil Třešňák, Jaromír Nohavica, Karel Plíhal, Slávek Janoušek, Jan Nedvěd...
  Students composing their own music, the structure of lyrics, harmonization, guitar and other accompanying instruments, principles of duets and turning poetry into music.
  Production of a folk concert, listener psychology.
  Computer music.
  Copyright.
  The ability to play a musical instrument is welcomed but is not necessary.

VB035 English I

z 0/2 1 kr., podzim

• Mgr. Eva Rudolfová - Mgr. Marcela Sekanina Vavřinová - Mgr. Zuzana Vašíčková - Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: The course is aimed at improving the knowledge of English, which should be intermediate at the beginning of the course. Students are allowed to attend the course after taking the entrance test in the first week of the semester.
• Goals: The course aims to broaden the knowledge of English language acquired at secondary school and to focus on specialized language in the area of IT, presentations, discussions and general academic language. At the end of the course students should be able to: understand specialized articles; use the language fluently and properly; talk about a wide range of IT related topics; provide relevant explanations and arguments; give clear descriptions and presentations; answer questions spontaneously.
• Learning outcomes: Students will be able to - communicate in English about their field of study; - write formal emails (requests, applications, complaints etc.); - understand spoken and written English on general and general academic level + their field of expertise; - present their ideas/ findings efficiently; - interact efficiently and politely with others - negotiate, debate, cooperate and solve problems constructively; - think critically and argue in an informed way; - plan and reflect, provide and receive feedback and act upon it.
• Syllabus: English for academic and specific purposes
  Grammar, vocabulary and phrases at B2 level and higher
  Formal language - register and usage
  Formal emails and providing feedback
  Reading and discussion of specialized texts

VB036 English II

z 0/2 1 kr., jaro

• Mgr. Lucie Procházková - Mgr. Eva Rudolfová - Mgr. Marcela Sekanina Vavřinová - Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: VB035 || souhlas
  The course is a follow-up to VB035 English I.
• Goals: VB036 aims to further broaden the knowledge of English grammar and phrases and to focus on IT related topics chosen by the students themselves. At the end of the course students should be able to: understand specialized articles; obtain information from highly specialized sources; give clear presentations; write a short formal email; provide relevant explanations and arguments; interact fluently and spontaneously.
• Learning outcomes: Students will be able to - communicate in English about their field of study; - write formal emails (requests, applications, complaints etc.); - understand spoken and written English on general and general academic level + their field of expertise; - present their ideas/ findings efficiently; - interact efficiently and politely with others - negotiate, debate, cooperate and solve problems constructively; - think critically and argue in an informed way; - plan and reflect, provide and receive feedback and act upon it.
• Syllabus: English for academic and specific purposes
  Grammar, vocabulary and phrases at B2 level and higher
  Presentations and class discussions on topics chosen by the students.
  Formal language - register and usage
  Reading and discussion of specialized texts

VB037 Writing in English

zk 0/2 2 kr., podzim

• Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: VB001
  VB001
• Goals: This course is designed to teach students the necessary skills that will enable them to proceed from sentence construction and paragraph writing to essay writing. The students will be familiarized with the writing of topic sentences, thesis statements, and different types of paragraphs and essays. The students will practice these steps of the writing process via in-class writing, text analysis, peer assessment, editing, and writing of a draft of the final essay. While some grammatical aspects of English used in the academia will be touched upon in the class, the students are expected to study individually in case they find their levels of knowledge not sufficient for class purposes. Importantly, however, mastering the variant of academic English used in computer science writing is not the primary objective of the class, as the class focuses on becoming familiar with formal written English as a means of expressing one's thoughts clearly and coherently. Nevertheless, many of the writing guidelines can be applied for computer science writing as well.
• Learning outcomes: Students will be able to construct a coherent and cohesive text written in standard academic English. They will be able to recognize that poor writing frequently results from a misuse of or over-reliance on certain language features, e.g. the passive voice, complex sentence structure, or nominalizations. Students will be then able to identify issues in a given text and suggest several ways of solving them. Finally, students will also understand that a text should follow a clear and well-organized structure, and they will also gain insight into drafting texts and their subsequent revisions.
• Syllabus: Basic academic English guidelines; academic vocabulary
  Paragraph writing - developing central idea, coherence, etc.
  Introduction and conclusion, thesis statement
  Writing your first draft
  Mechanics and clarity of writing
  Writing effectively
  Writing the final essay

VB039 Presentations in English I

k 0/2 2 kr., podzim

• Mgr. Eva Rudolfová
• Goals: VB039 is a course for all students who need to speak in English more. Its aim is to give students a lot of practice in advanced language and communication skills and to help them communicate more effectively by improving their grammatical knowledge and developing IT-related vocabulary. It can be used as an additional course to VB035 (which has classes only every other week) or at any point in your studies when you want more confidence in presenting your professional and academic ideas in English. Main objectives can be summarized as follows: to increase your active IT vocabulary; to develop essential communication skills such as giving presentations and taking part in discussions; to improve fluency through discussion activities; to give confidence in using English.
• Learning outcomes: to increase your active IT vocabulary; to develop essential communication skills such as giving presentations and taking part in discussions; to improve fluency through discussion activities; to give confidence in using English.
• Syllabus: Tailored to students´ needs It is set up at the beginning of each term by the class and the teacher, taking into account the individual needs of particular students. It includes areas related to speaking with confidence in the academic and professional world, presenting ideas, opinions, trends and visuals, as well as everything related to presentation skills in English. If needed, the classes also discuss related soft skills such as handling nervousness and stage fright, creating a good presentation presence and many other.

VB040 Presentations in English II

k 0/2 2 kr., jaro

• Goals: VB040 is a course for all students who want to improve their presentation skills. Its aim is to give students a lot of practice in advanced language and communication skills and to help them communicate more effectively by improving their grammatical knowledge and developing IT-related vocabulary. It can be used as an additional course to VB036 (which has classes only every other week) or at any point in your studies when you want more confidence in presenting your professional and academic ideas in English. Main objectives can be summarized as follows: to increase your active IT vocabulary; to develop essential communication skills such as giving presentations and taking part in discussions; to improve fluency through discussion activities; to give confidence in using English.
• Learning outcomes: Main objectives of the course can be summarized as follows: to develop communications skills (taking part in discussions and giving a short presentation); to improve fluency through discussion activities; to increase IT vocabulary; to create confidence in using the language.
• Syllabus: Tailored to students´ needs It is set up at the beginning of each term by the class and the teacher, taking into account the individual needs of particular students. It includes areas related to speaking with confidence in the academic and professional world, presenting ideas, opinions, trends and visuals, as well as everything related to presentation skills in English. If needed, the classes also discuss related soft skills such as handling nervousness and stage fright, creating a good presentation presence and many other.

VB041 The Principles of Legal Reasoning

k 2/0 2 kr., podzim

• prof. JUDr. Ivo Telec, CSc.
• Goals: Introduction to legal thinking.
• Learning outcomes: At the end of the course students should be able to: understand the basic nature of the legal thinking and reasoning; understand, discuss and explaine the nature of the natural rights and legal principles; explaine the methods of legal philosophy and jurisprudence; analyse and judge the strategy of the legal protection of personality;
• Syllabus: Introduction to the legal education; The legal philosophical introduction and approach; The globalization and europeisation of law, espec. of the private law The natural law matter (the basic issues); The legal principles and their notion; The interpretation of law; especially of the private law The general overview of the jurisprudential tests (methods), f. i. the test of proportionality etc. The natural personality rights and their state protection (the Czech example);

VB042 Intellectual Property

zk 2/0 2 kr., jaro

• prof. JUDr. Ivo Telec, CSc.
• Goals: The goal of this course is that students are able to: discuss the Czech intellectual property law in its international and communitarian framework; name, describe, calculate, explaine, differentiate, arrange and analyse the intellectual property rights and the basic elements of the protected objects; understand the legal dispositions with the protected objects and to apply this; discuss, analyse and judge the legal strategy of the intellectual property rights enforcement;
• Learning outcomes: At the end of the course students should be able to: discuss the Czech intellectual property law in its international and communitarian framework; name, describe, calculate, explaine, differentiate, arrange and analyse the intellectual property rights and the basic elements of the protected objects; understand the legal dispositions with the protected objects and to apply this; discuss, analyse and judge the legal strategy of the intellectual property rights enforcement;
• Syllabus: Introduction to the intellectual property law study: the aim, history, system, sources, international organisations (WIPO, WTO, EPO, UNESCO), constitutional and moral basis, public administration of the industrial property rights
  The basic elements of protected objects
  The exercising of intellectual property rights
  The enforcement of intellectual property rights
  Industrial property rights
  Copyright and neighbouring rights including the collective management of rights

VV015 Political Science

z 2/0 2 kr., podzim

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: Interest in temporarily conditioned changes of the phenomenon of politics is expected. There are various enjambments from other spheres of human activities in politics preventing the understanding of fundamental ideas in it and the risks connected with it.
• Goals: Science of politics is here taken as a historically conditioned and steadily topical issue of changing presuppositions structuring and reflecting political might. It traces the development from the antique Greek democracy till contemporaneity (with parallel enjambments in our time). Continuous commenting of weighty news characterising the common "roots" coupled with them, has been considered.
• Learning outcomes: Basic orientation in politology.
• Syllabus: The subject, basic concepts, and function of politology. The individual and his/her society.
  Presuppositions of the origin of the old Greek democracy. The Greek-Persian Wars and the problem of hegemony. The big "Pelopponessos" quest.
  Political ideals of Plato and Aristotle.
  The Pax Romana. St. Augustin.
  The fighting over investiture. The Constitution of Venice.
  The Hussite Revolution. Humanism and Reformation as programs of social reform. Machiavelli. Luther and Calvin. Social utopia (Morus, Bacon, Campanella, Comenius).
  The beginnings of modern legal thinking (Bodin, Althusius, Grotius). Peace of Westphalia.
  The background of the "Big Rebellion" in the 17-th-century England . The English Parliamentarism. Hobbes, Milton, Harrington.
  Continental Europe in the second half of the 17-th century. The outcome of the English "Glorious Revolution". Locke.
  The Enlightenment (i.e., the beginning of modern political times). The French Revolution. The Congress of Vienna.
  The predominant position of Great Britain. The formation of the Italian and German states in the second half of the 19-th century. The Austrian-Hungarian Settlement.
  The causes of WWI and WWII and their outcome. The so-called Cold War. The fall of the Iron Curtain and the doom of the Soviet Union.
  A dramatic economical rise of China. BRIC. Globalization.
  A clash of civilizations. Our contemporaneity.
  The aim of these lectures is a clarification of the basic concepts of politics as well as of the structure and teleology of power. A historical explanation seems to be the best method of how to follow the dramatic tension between the formulated goals and values to be reached, always in another way and in another preferential sequence.

VV018 Topics in Religionistics

z 2/0 2 kr., jaro

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: It is recommended, though not obligatory, to start VV018 after VV014.
• Goals: In comparison with course VV014 this subject more heavily counts with due familiarization with relevant religious texts and their interpretation. In accord with shown interest of the participants some other themes (not specified by the lecture structure) may be introduced. Contemporary sects will not be overlooked.
• Learning outcomes: The student will be adequately able to appraise this weighty field and, simultaneously, to argue in it adequately and without scrupples.
• Syllabus: On the basis of the initial lectures (but also without having passed through them) it has been intended here - partly in workshop form - to deepen the knowledge in this sphere, and that through the relevant texts.
  The Old Testamental tradition, e.g., will be illustrated by the starting chapters of the Book of Genesis and the Book of Job, Christianity will be characterized by the final chapters of Matthew and Mark, and the Letters of St. Paul (Romans, 1 Cor.).
  The critical heritage of Hume (and Mill) and Masaryk's relation to religion (considering Čapek's "Discussions with TGM", too) will be taken into account.
  The Orient is to be introduced by passages from the Upanishads and the Bhagavad Gita, and we shall try to somewhat understand the unknown world of tao and zen.
  A choice of texts (Kierkegaard, Russell, Moody etc.) is to serve as a stimulus for considerations on the impact of rationality in religion.

VV019 Selected chapters in politology

z 2/0 2 kr., jaro

• prof. PhDr. Ing. Miloslav Dokulil, DrSc.
• Prerequisities: The course thematically follows VV015; its passing is not obligatory, but recomendable.
• Goals: Political terms/concepts are based in their historically given background (so as it has been the case with the initíal course). Their analysis illustrated by contemporary material makes possible a reasonable orientation and choice in political problems. An analysis of contemporary social and political problems is the starting point; the past has often been the clue towards the understanding of today's questions.
• Learning outcomes: Students will understand selected aspects of today's politology.
• Syllabus: The beginnings of Political New Ages.
  The American experience (Madison, Hamilton, Jay, Paine and the American Constitution). Its resonance in the works by Tocqueville. The problems of "majority rule". The status of "federation" and the "sovereignty" of the particular colonies (republics). An example for the EU?
  Great Britain and Central Europe under the influence of Enlightenment and in confrontation with the French Revolution. - Montesquieu. Burke. Tocqueville.
  The "European balance of power" in the 19-th century.
  From conservatism via liberalism to Marxism? J. St. Mill, "On Liberty".
  The re-grouping of forces after 1848. Imperialism?
  WWI and the re-arrangement of Europe after the war. Political ideologies in between of the two world wars. - Toynbee, Sspengler. Fascism, nacism, communism, Trotskyism.
  The second global conflict of war in the 20-th century and its political and ideological outcome. The formation of the "Two Camps".
  Towards a United Europe? - The end of colonialism? The problem of toleration. The disintegration of the so-called Eastern Bloc. Terrorism.
  Conclusion: New centres of power and new ideas? Liberalism again? Tiredness of democracy? Is corruption to win over? The end of American Hegemony? (Arendt, Orwell, Fukuyama, Huntington, Chomsky etc.)

VV024 Interpretation of Texts

k 1/1 2 kr., podzim

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: The subject represents the continuation of Academic Style Basics Course by stressing the esthetic function of texts during their analysis; Introductory lectures deal with analytical approaches to, and theoretical reflections of, a literary text; structuralist and semiological aspects ; Czech literary and esthetic inspiration; The analysis of the text as information; orientation in dominant and alternative paradigms of literary communication; investigation of contents analysis limits and interpretation ensue; aspects of literary communication, the course pays attention mainly to the author and reader/listener in the communicative perspective of the text, to strata of textual structure; unifying utterance perspectives; so-called adoption; after the theoretical part, students apply the acquired knowledge to their own analysis of a chosen text.
• Learning outcomes: Student will be able to:
  explain the context of the literary text and the pitfalls of its exploration as information;
  analyze art text plane of the text structure;
  justify the pitfalls of the composition of a literary work;
  demonstrate the individuality of the individual appropriation of the artistic text.
• Syllabus: Critical analyses of accepted and controversial pieces of contemporary Czech and world literature.
  How to read a literary text, how to comprehend it, how to write a review.
  Movies based on literary works.
  Creative works by students.
  The works studied are in accordance with the student's interests, e.g. Jáchym Topol, Zdeněk Rotrekl, Jan Skácel, Alexandra Berková, Jiří Kratochvil, William Styron, John Irwing, Umberto Eco, Konrad Lorenz, Carl Gustav Jung ...
  The forms of essay, short stories and novella.
  The composition and design of a novel, dialog building.
  Written and spoken polemics.
  Report.

VV026 Creative Writing Workshop

k 1/1 2 kr., jaro

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: strives after arousing the students' creativity by means of their own artistic activity (mainly literary); generate an interest in the active and non-consumer attitude to life both in oneself and other people. At the end of the course students should be able to understand and explain sense of artistic activity; create their own artwork in field of literature; interpret actual artistic activity.
• Learning outcomes: Student will be able to:
  explain creative approach, eclectic, compilation;
  practically apply theme selection, information gathering, study and empathy, writing stimulation, collection and sorting of material;
  to clarify inspiration through science, literature, painting, music, architecture;
  to demonstrate a collage of both own and foreign texts.
• Syllabus: The point in writing, catharsis, graphomania
  What to write about (finding a topic)¨
  Brainstorming
  Different approaches: creative, eclectic, compilational
  Choosing a topic, collecting info, study and empathy, syllabus
  Non-literary texts (non fiction)
  Automatic writing
  Metaphor creation
  Inspiration from science, literary texts, painting, architecture
  Diary and its forms
  Collage of ones own and other texts
  Collective writing
  Change of perspective, change of tense
  Choice of genre and its changes
  Variations, imitations, parody
  Plagiarism
  Manuscript, the first draft
  Language games and reproduction exercises
  Theatre performance
  Text reviewing and editing, compositional and stylistic amendments, corrections, annotation, information about the author
  Author's reading
  Critical evaluation, polemic, the ethics of critisism
  Copyright
  Book presentation
  Texts on the Internet
  A set of texts written by the students throughout the course

VV027 Postmodern culture

z 1/1 2 kr., jaro

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: orientation in postmodern culture. It is based on not-only-Czech philosophical and culturally historical background. It endeavors after the critique of the consumer conception of life as well as comprehension of racist and xenophobic pathology via new art and multimedia means. A part of the course is the observation of current cultural events. At the end of the course students should be able to understand and explain postmodern culture; interpret actual artistic activity.
• Learning outcomes: Student will be able to:
  to define the philosophical basis of postmodern culture;
  to distinguish kitsch and consumer culture;
  to evaluate new arts and multimedia means of expression;
  clarifying vision as empowering the world - loss of gnoseological concept, interactive understanding of our position in the world, offensive nature of visual perception, character functionality, language functionality, language of media, social value of virtual reality, world of visual characters, new concept of reality.
• Syllabus: Laws of the development of styles in cultural and social epochs
  Modern and modernization
  Cultural outsiders vs. oficial production
  About nature of our culture
  The philosophical bases of postmodern culture
  Postmodern as a self-criticism of modern
  Psychological bases of culture
  Modern vs. postmodern culture
  Postmodern culture in literature, music, fine arts, architecture and popular culture
  Junk art and consumer culture
  Alternative and new culture
  Underground, videos, commercials apparent and hidden, interdomain works, one artistic branch melting into another, the so-called new arts and multimedia modes of expression
  Postmodern culture in a sociological approach
  Human personality in postmodern times
  Feminism and sexual harassment
  The pathology of man's efficiency, racism and xenophobia, the myth of supermen and androgyns

VV028 Psychology in Informatics

z 1/1 2 kr., podzim

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: some basic information concerning the psychological aspects of the impact of new information technology on the individual's personality; psychology of electronic communication; psychological aspects of computer games; personality of professionals in communication technology; impact of computers on education in the new information era. At the end of the course students should be able to understand and explain psychological aspects of the impact of new information technology on the individual's personality; make deductions based on acquired knowledge and understand problems that will arise with new technology assembly.
• Learning outcomes: Student will be able to:
  in its own words to explain the computer view of the world;
  to analyze the phenomenon of electronic communication and its influence on the psychology of communication;
  to demonstrate practical skills in the psychology of interpersonal communication;
  to put the pros and cons of computer games from a psychological point of view.
• Syllabus: Transactional analysis
  Stress and dealing with it
  Psychopathology and methods of therapy
  Mental health care
  Social beliefs and attitudes, interpersonal attraction
  Social interaction and influence - the presence of other people, its effect, group decisions
  Relations between people and machines
  Social relations and team-work, communicativeness
  Verbal and nonverbal communications at work
  Assertiveness
  Solving a conflict and problem situations
  The strategy of conducting competitions for leading posts

VV031 Basics of Fine Art I

z 2/0 1 kr., podzim

• Mgr. Markéta Žáčková - Mgr. Renata Šuráňová
• Goals: At the end student will be able to interpret visual art in relations since year 1500 till now.
• Learning outcomes: At the end student will be able to interpret visual art in relations since year 1500 till now.
• Syllabus: This two-term course consists of the series of lectures accompanied with excursions to Brno exhibition institutions and art-important architectonic objects. There are 10 lectures and three excursions each turn. Lectures are given also by external experts. In the first turn students are introduced to the basic evelution of european art and architecture since the middleage. After course completion, students are able of basic orientation in art evolution and they are able to give interpretation to various visual forms. At the same time they are acquainted with the fundamental terms and categories in the history of art.

VV032 Introduction to History of Fine Art II

k 2/0 2 kr., jaro

• Mgr. Renata Šuráňová - Mgr. Markéta Žáčková
• Prerequisities: VV031
  Successfully pass VV031.
• Goals: At the end student will be able to interpret visual art in relations since year 1500 till now.
• Learning outcomes: At the end student will be able to interpret visual art in relations since year 1500 till now.
• Syllabus: This two-term course consists of the series of lectures accompanied with excursions to Brno exhibition institutions and art-important architectonic objects. There are 10 lectures and three excursions each turn. Lectures are given also by external experts. In the first turn students are introduced to the basic evelution of european art and architecture since the middleage. After course completion, students are able of basic orientation in art evolution and they are able to give interpretation to various visual forms. At the same time they are acquainted with the fundamental terms and categories in the history of art.

VV033 Photography

k 1/1 2 kr., podzim

• Mgr. Jiří Víšek
• Prerequisities: ( PV123 || VV042 || PV156 )&& SOUHLAS
  Course requires photographic vision, previous experience (including non professional) is welcome. Digital SLR suggested for assignments.
• Goals: Fundamentals of photography: composition and light in digital studio photography. By the end of the course, the student will understand photometry and the basics of working with light. The student will produce photographs in the following categories: Outline, Light I (dispersed light, lateral light, point light, depiction by light), Still Life. The students will produce their own photo collections.
• Learning outcomes: Student will be able to work with light setup for the still-life in the photo studio with the continual anf flash light, thus create studio photo with high quality.
• Syllabus: Basics of the optics theory and photo mechanics
  Exposure basics
  Basics of studio lighting
  Image composition
  Tonality and linear perspective, sharpness/unsharpness, contrast, rythm
  Emotional and informative message in photography
  Color composition, color perspective, color contrast and dominance of color

VV034 Photography II

zk 1/1 2 kr., jaro

• Mgr. Jiří Víšek
• Prerequisities: souhlas
  Course requires photographic vision. Digital SLR suggested for assignments. Prerequisite VV033
• Goals: Follows the course Photography I, focused on work in the studio and on location. By the end of the course, the student will be able to produce a collection of photographs in the following categories: Figure in Studio I, Macrophotography, Portrait I. Students will grasp the stylization factors of taking a picture.
• Learning outcomes: Student willbe able to work with basic effects in the studio photo such as optical and motion blur, multiple exposition, low and high exposition, depth of field.
• Syllabus: Photograpy genres:
  Still life
  Landscapes
  Photojournalism and documentary photography
  Portrait and nude
  Commercial photography
  Photographs of architecture and sculpture

VV035 3D Character Modeling

k 1/1 1 kr., podzim

• MgA. Helena Lukášová, ArtD.
• Prerequisities: souhlas
  Interest in digital 3D modelling applications, creative thinking, independent work on assignments.
• Goals: The aim of the course is to explain principles of 3D modelling, how to create an organic form, especially the characters in the 3D modelling program. The anatomy of the human body is explained in relation to the 3D modelling techniques. Students are working independently under the teacher's supervision. The presentation of the model - lights, composition, rendering is also explained. There are also lectures explaining modelling techniques and explanation of the human anatomy with examples from art history. The work of CG artists is also introduced. The course is designed to include the explanation of realization of the model in the material through rapid prototyping methods.
• Learning outcomes: The student will learn about the state of the art of contemporary methods for creating 3D characters, will understand terminology. The main outcome is the results of the individual student projects which can be used as the basis for the individual portfolio for personal presentation.
• Syllabus: Proportion of the human body
  Modelling of the organic form in 3D modelling programs
  Human head anatomy
  Low Poly model Modelling of the according to photo references
  Model presentation- lights, composition, render
  Creative work with the finished model, deformation tools.
  Preparation of the 3D model for realization through rapid prototyping methods

VV036 3D Character Modeling II

zk 1/1 2 kr., jaro

• MgA. Helena Lukášová, ArtD.
• Prerequisities: souhlas
  Prerequisite: VV035 3D Character Modeling
• Goals: Building upon Art Anatomy I, the main aim of the course is to capture the character; students independently work with human proportions, typologies, deformations, etc. in 3D modeling programs. The work on individual projects is complemented by lectures on deliberate deformation and idealization of a human figure, beauty, and fashion, combining atropomorphic and zoomorphic aspects within the frame of character formation. Students are led to independent creative work. An important part is also the preparation of the virtual model for the rapid prototyping (STL Check, retropologisation, optimization).
• Learning outcomes: A capability of standalone work with visual modelling tools.
• Syllabus: Typology of a human figure.
  Growth periods. Individuality and a cartoon.
  An idealization of human body and clothing.
  Animal anatomy.
  Creating a character based on existing knowledge.
  Completing a 3D character model from the previous semester.
  Creating a Hight Poly model
  Fundamentals of Animation
  Preparation of a model for rapid prototyping.

VV039 Plein Air

k 0/0 2 kr., jaro

• MgA. Helena Lukášová, ArtD.
• Prerequisities: PV067 || PV083 || PV085 || VV034 && souhlas
  The prerequisite for this course is the interest of the student to activly participate on the realisation of the project, desire to experiment and work in team.
• Goals: The aim of the course is to encourage the creative potential and conceptual thinking ,interaction with the unknown environment, team work. Students will change the supervisors in the beginning so they learn the foundation of drawing and photography on which they will base their own creative approaches and projects. We want to lead students to form their own way of expression and experimentation. Students will build their self-confidence in the creative process interpreting the environment and learn to work in team.
• Learning outcomes: Student will have the experience with creation and realisation of a project in team, will experiment with various technique and experimental strategies, will be able to adopt and react to the given possibilities of the environmet (plain-air).
• Syllabus: LANDSCAPE landscape drawing - linear and atmospheric perspective, photographing the landscape - landscape detail, architectural detail DRAWING - as a record, frottage, the anstraction of the landscape PHOTO - colour filters, camera obscura, light drawing, experimenting with flash, moving blur SITE SPECIFIC PROJECTS - subtle interventions into the environment, space, landscape Konceptual SELFPORTRAIT AND PORTRAIT - adaptation. the idea of identity in the unknown environment and the means of its understanding - simplification. mimickers, contrast, empathy PERFORMANCE, HAPPENING - keeping diary (audio, video) stylized "fake" documentary EXPERIMENTAL TYPOGRAPHY

VV040 Theater Play

k 0/2 2 kr., jaro

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: Main objectives can be summarized as follows: Students' theater performance training and realization in honour of the Dies Academicus Brunensis annual event. At the end of the course students should be able to create dramatical role; understand and explain trends of the contemporary theater.
• Learning outcomes: Student will be able to:
  to take on a particular theatrical role;
  define the role of theater dramaturgy;
  to analyze a specific theatrical inscenation;
  to demonstrate their own creative approach to the theater.
• Syllabus: Students' theater performance will be trained during the semester, with its mid-May premiere at the Dies Academicus Brunensis event. The premiere will be held at the Faculty of Informatics, closing performance is supposed to happen at HaDivadlo od Husa-na-provázku theaters
  Rehearsals are every Wednesday starting from 6p.m., the weekend before the premiere is allocated for dry run
  In the begining of the semester a casting will happen; those who will not pass through recruitment may integrate within the organizing team (scene building, backdrop)
  The course is open to the whole University, teacher's approval is needed for registration.

VV041 English for Academic Purposes

z 0/2 2 kr., podzim

• Anjuli Pandavar, PhD
• Prerequisities: English - B2 CEFR level and above
• Goals: This is a blended-learning course intended for students and academic professionals who want to become acquainted with the basic principles of the art and science of public speaking in English language. The class meets once a week for two hours to undertake diverse activities with the aim to learn about creating and delivering effective talks. The course materials present useful guidelines and generally accepted criteria on how to conduct an audience analysis, how to develop content and structure it for maximum impact, how to create and effectively use visual aids that support your ideas, how to handle tough questions and, of course, it suggests which critical mistakes and common traps to avoid. Presentations are practiced in contact lessons while the distance learning component is mediated through discussion forum and wiki activities within the IS MU and/or Moodle. We hope that you will enjoy this course and discover that public speaking is considerably more exciting, enjoyable and encouraging experience that you thought beforehand.
• Learning outcomes: This is a blended-learning course intended for students and academic professionals who want to become acquainted with the basic principles of the art and science of public speaking in English language.
• Syllabus: Seminar I – Introduction to Academic Public Speaking; Seminar II –Theory, General Characteristics and Preparation; Seminar III - Introduction; Main Body; Audiovisual aids and Ending; Seminar IV – Questions; Delivery and Critical listening and evaluation; Seminar V – XII Practical exercises

VV042 History of Photography

z 2/0 2 kr., jaro

• Mgr. Jiří Víšek
• Prerequisities: The course targets Graphic Design and Multimedia students interested in photography, also for other students of Faculty of Informatics and Masaryk’s University
• Goals: Brief summary of the history of photography from the beginning up to the present. By the end of the course, the student will be able to write an essay on an established photographer, and to use the information about the creative process of a known photographer for his/her own photography work.
• Learning outcomes: Student will gain knowledge about the history of photography from its beginning till contemporary photography, will be oriented in the variuos themes of the disciplin, also will be informed about the optical and technical development.
• Syllabus: Photography as a visual art.
  Photographic terminology.
  Photographic genres and themes.
  Origins of photography.
  Portrait photographers of 19th century
  Pictorialism.
  Birth of modern photography in U.S.A., Germany and Czech.
  Photography between the wars; avant-garde photography.
  Landscape photography.
  Documentary and social documentary photography at the turn of 19th and 20th century.
  War photography.
  Czech humanistic photography.
  Fashion and commercial photography.
  Current trends worldwide, current trends in Czech photography.

VV043 Academic Writing in English

z 0/2 5 kr., jaro

• Daniel Gerrard, M.A.
• Prerequisities: typ_studia ( D ) || souhlas
  At least B2 CEFR level and some experience with academic writing.
• Goals: There is an increasing need among doctoral candidates to publish their work in various types of academic publications and engage with a wider range of academic, professional and public audiences. The goal of this course is to familiarize doctoral candidates with different approaches to scientific writing, take their academic writing skills in English to a higher level and offer them a range of tools to adapt their focus of language to address their target readers at specific, multi-disciplinary and general levels. The course addresses firstly the context of scientific writing to situate the styles of writing that doctoral candidates are working with. It will discuss aspects of clear and concise writing style, and lexical and discourse relationship patterns in academic text, along with functional perspectives for positioning and structuring information and argument in the wider scope of thesis and journal article writing.
• Learning outcomes: By the end of the course, participants will be able to use academic and technical vocabulary; read and analyze texts to make use of them in writing; understand different text styles and structures; write successful titles, abstracts, paragraphs, and individual sections of a thesis or journal article; and provide and respond to peer feedback.
• Syllabus: Academic style
  Academic and technical vocabulary
  Plagiarism and referencing
  Paragraphing
  Academic text types
  Summarising and paraphrasing
  Writing a critique
  Peer review
  Abstracts
  Sections of a thesis and journal article
  Editing and proofreading

VV045 Photography III

zk 1/1 2 kr., podzim

• Mgr. Jiří Víšek
• Prerequisities: souhlas
  Lessons of subject Photograph assumes photographic perception of world. Using of own digital is suitable for practise, single-lens reflex camera with replaceable optic is the best. VV034
• Goals: Selective photography course aimed at individual work in each photography genre. By the end of the course, the student will be able to produce: a study of a figure in a studio, a montage of figures on a white background, a portrait lit with several light sources, a tabletop, and a collection of theatre photography.
• Learning outcomes: Student will be able create good light composition for the portraiture studio photo. Also student with the experience from the course will be able to pursue his/her own carrier in documentary or artistic photography.
• Syllabus: Model in studio.
  Portrait and self-portrait.
  Landscape.
  Urban landscape.
  Social documentary.
  Creating personal work.
  Documentary photography.
  Photography in theatre.

VV050 Motion Design

k 1/1 2 kr., podzim

• MgA. Kateřina Spáčilová
• Prerequisities: souhlas
  The animation and Visualisation course is based on the understanding of animation techniques. The interest and artistic approach is expected. Students are obligated to prepare reference/material for finalizing projects in other time than the time when the course is running.
• Goals: First projects are created manually for the understanding of phasing and movement dynamics. Than this projects are transferred to a digital file and consequently finalized digitally in animation software. The understanding of animation basics and consequent incorporation of digital editing in projects are expected. During the course, the history of animation and visualization will be presented and actual trends in animation in the age of new media will be discussed also. The understanding of the principles of animation based on historical references is incorporated into the digital methods of production.
• Learning outcomes: The outcome of the course is the results of various assignments in the form of video - animation. These animations can become the part of the personal portfolio for presentation.
• Syllabus: Principles of cartoon animation-phasing Typographic animation Post-production with scanners and cameras Basics of Adobe After Effect

VV051 Animation

k 1/1 2 kr., jaro

• MgA. Kateřina Spáčilová
• Prerequisities: VV050 && souhlas
  Artistic talent, project completion.
• Goals: Follow up to VV050 Animation and Visualization I. Students will gain a deeper theoretical and practical knowledge to create film clip.
• Learning outcomes: Experience with a movie clip creation.
• Syllabus: Film and animation preview.
  Film plot analysis.
  Technical script.
  Visualization based on music.
  Script and clip production.

VV052 Evening Drawing

k 0/2 2 kr., podzim

• MgA. Helena Lukášová, ArtD.
• Prerequisities: souhlas
  Subject "Drawing/ evening class" pressuposes a creativity as well as respecting the nature of the subject including a manual work depending on a set task.
• Goals: At the end of the course students should be able to draw human figure in different styles. They will practise drawing of a woman and man model standing, sitting, lying. They will be able to draw with charcoal, graphite, red chalk and crayon.
• Learning outcomes: During the semetr students will create the serie of figurative drawings, acquire the experience with the anatomy, will gain experience with drawing larger formats. This experience will help students to create more professional conceptual drawing s in other areas - story-board, stop motion animation, conceptual drawing for graphic design etc.
• Syllabus: Human figure drawing with live model; standing, sitting, lying.
  Nude; woman and man; standing, sitting, lying.
  Human head drawing: woman, man, infant, senior.
  Quick sketch
  Movement study

VV052 Evening Drawing

k 0/2 2 kr., jaro

• MgA. Helena Lukášová, ArtD.
• Prerequisities: souhlas
  Subject "Drawing/ evening class" pressuposes a creativity as well as respecting the nature of the subject including a manual work depending on a set task.
• Goals: At the end of the course students should be able to draw human figure in different styles. They will practise rawing of a woman and man model standing, sitting, lying. They will be able to draw with charcoal, graphite, red chalk and crayon.
• Learning outcomes: During the semetr students wiil create the serie of figurative drawings, acquire the exoerience with the anatomy, will gain experience with drawing larger formats. This experience will help students to create more professional conceptual drawing s in other areas - story board, stop motion animation, conceptual drawing for graphic design etc.
• Syllabus: Human figure drawing with live model; standing, sitting, lying.
  Nude; woman and man; standing, sitting, lying.
  Human head drawing: woman, man, infant, senior.
  Quick sketch
  Movement study

VV063 Computers and Ergonomy

k 1/1 2 kr., podzim

• PaedDr. Hana Vrtělová
• Goals: Aim of the course is to teach the student to understand the basic principles of working ergonomy with PC and working desk techniques, to evaluate concrete working conditions and to prevent health impairment.
• Learning outcomes: Successful graduates will gain:
  understanding of basic principles of ergonomics of competer workplace;
  some practical exercsises for correction of body deformation due to office work.
• Syllabus: 1. Theory: The Introduce. Ergonomy of the office workplace I.Practice: Ergonomic evaluation of the sulf workplace. 2. Theory: Ergonomy of the office wolkplace II (quality of indoo environment) Practice: Ergonomic simple ways improoving the workplace. Exercise with overballs. 3. Theory: Functional anathomy of the musculo-sceletal system. Practice: exercises for individual muscular groups. 4. Theory: Musculosceletar dysbalances. Practice: Tests of muscular dysbalances. 5. Theory: Biomechanic of musculosceletal system: Practice: Tests of muscular dysbalances - continue. 6. Theory: Right and wrong hold the body, stereotypes of mooving. Practice: Exercises for compensation of the wronghold of the body. 7.Theory: Functional anathomy of the musculosceletal system II: Physiology of the blood circulation. Practice: Exercises for the prevention of the blood stasis. 8. Theory: Repetitive strain injury (RSI) Syndrome. Practice: Exercises for compensation. 9. Theory: Pain and musculosceletal system. Practice: Exercises for compensation. 10.Theory: "The school of back". Practice: The right hold of the body during the different physical activities. 11. Theory: Fatigue, its sources and manifestations. Practice: Exercises for relaxation during the work with PC. 12. Stress, psychosocial load. Practice: Exercises for relaxation. 13. The load for eyes during the work with PC. Practice: Exercises for the decreasing of the eyes load. 14. Theory: The most common health problems during the occupational activities using PC. Practice: Exercises for compensation. 15. Theory: Nutrition for sedentary work. Practice: Self evaluation of nutritional habit, comparrison with dietary guidelines.

VV063 Computers and Ergonomy

k 1/1 2 kr., jaro

• PaedDr. Hana Vrtělová
• Goals: Aim of the course is to teach the student to understand the basic principles of working ergonomy with PC and working desk techniques, to evaluate concrete working conditions and to prevent health impairment.
• Learning outcomes: Successful graduates will gain:
  understanding of basic principles of ergonomics of competer workplace;
  some practical exercsises for correction of body deformation due to office work.
• Syllabus: 1. Theory: The Introduce. Ergonomy of the office workplace I.Practice: Ergonomic evaluation of the sulf workplace. 2. Theory: Ergonomy of the office wolkplace II (quality of indoo environment) Practice: Ergonomic simple ways improoving the workplace. Exercise with overballs. 3. Theory: Functional anathomy of the musculo-sceletal system. Practice: exercises for individual muscular groups. 4. Theory: Musculosceletar dysbalances. Practice: Tests of muscular dysbalances. 5. Theory: Biomechanic of musculosceletal system: Practice: Tests of muscular dysbalances - continue. 6. Theory: Right and wrong hold the body, stereotypes of mooving. Practice: Exercises for compensation of the wronghold of the body. 7.Theory: Functional anathomy of the musculosceletal system II: Physiology of the blood circulation. Practice: Exercises for the prevention of the blood stasis. 8. Theory: Repetitive strain injury (RSI) Syndrome. Practice: Exercises for compensation. 9. Theory: Pain and musculosceletal system. Practice: Exercises for compensation. 10.Theory: "The school of back". Practice: The right hold of the body during the different physical activities. 11. Theory: Fatigue, its sources and manifestations. Practice: Exercises for relaxation during the work with PC. 12. Stress, psychosocial load. Practice: Exercises for relaxation. 13. The load for eyes during the work with PC. Practice: Exercises for the decreasing of the eyes load. 14. Theory: The most common health problems during the occupational activities using PC. Practice: Exercises for compensation. 15. Theory: Nutrition for sedentary work. Practice: Self evaluation of nutritional habit, comparrison with dietary guidelines.

VV064 Academic and Professional Skills in English for IT

zk 0/2 2 kr., jaro

• Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: VB001
  The prerequisite for enrolling in the course is passing the examination in English (VB001).
• Goals: The course aims at giving a well-rounded background in using English suited for both academic and professional area. One of the main focus of the course is formal and informal language and the fact that both have their places in professional and, to lesser extent, academic contexts. As there are multiple ways of maintaining formality, a proper grasp of its use can is needed to successfully navigate the complexities of everyday experiences in academia and professional work. Ultimately, formal and informal language are about presenting oneself to the world; as a result, presentations themselves as well as the ability to effectively summarize information will also be covered in the course. In other words, the course aims at improving not only the more language-oriented aspects of formal and informal English, but also the more abstract ways of thinking about oneself and the self's relation to the outside world.
• Learning outcomes: At the end of the course students should be able to: use appropriate register for a given language situation; compose well-structured letters essential for studies and workplace; effectively summarize information in speech and writing; give well-organized presentations; think about their approach to various tasks in academia and professions
• Syllabus: Appropriate register (formal/informal language)
  Writing professional letters
  Understanding summaries
  Giving presentations

VV067 Concept and Intermedia I

k 0/2 2 kr., podzim

• MgA. Anna Boček Ronovská, Ph.D.
• Prerequisities: souhlas
  Prerequisite - some of the courses of the Atelier of Graphic design and Multimedia
• Goals: The aim of the course is to introduce students to conceptual approaches in a creative process. It will help them to develop their own strategies in the incorporation of intermedia in their own student projects, which would be individual or in the group, where students will collaborate. Beside the work on the given assignment, there will be lectures introducing contemporary art with the emphasis on new media and digital technologies, to help them to understand the current situation.
• Learning outcomes: The student acquires knowledge about contemporary fine art and understands it in context with the art history of the twentieth century. The student will be able to use various strategies based on conceptual and intermedia in various fields such as viral campaigns, fine art etc. In summary, the student will gain self-confidence in his/her creative potential, will be able to work in a team on a creative project.
• Syllabus: 1. Conceptual work, idea and realization, a format of an idea as a sustainable medium and as the starting point 2. Record and its shifts (photography, diary, video) - an ongoing project 3. Text, notions, their meaning and their incorporation in the visual form 4. Automatic techniques, drawings, and paintings 5. Graphic techniques on the fringe and public space (comics, graffiti, street art)

VV068 Concept and Intermedia II

k 0/2 2 kr., jaro

• MgA. Anna Boček Ronovská, Ph.D.
• Prerequisities: souhlas
  Prerequisite: VV067 Conceptual and Intermedia Art I
• Goals: The combination of lectures and students work on their own or commonly given projects under the supervision of the teacher. He/she also brings the themes to be worked on with the explanation of possible strategies. The teacher will discuss specific problems which different types of the project brings up individually. The teacher works individually with the student and motivates them to work creatively. Students are expected to incorporate the knowledge of digital media they are familiar with (photography, audiovisual techniques, 3D modeling, manipulation of the digital image, vector graphic, drawing etc.) Students will consult with the teacher, study material will be recommended. Finished projects will be presented publicly such as projections, exhibitions, documentation.
• Learning outcomes: Gain knowledge allows students to work in multimedia space, for broadcasting companies, museums, advertising companies, etc. A student will be able to pick the optimal solution related to audio-visual project respecting the team spirit.
• Syllabus: Illusion, reality, indifferent spaces
  Performance and action, movement and visual interaction in the space
  Bricolage object and installation (incorporating found and untraditional materials)
  Opposites, work in contradicting formats
  Vanitas and the fourth dimension: timeline and ephemeral moment
  Author's film, collective project, teamwork

VV070 Seminar on Master's Thesis Writing

z 1/1 2 kr., podzim

• Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: VB001
  The prerequisite for enrolling in the course is passing the examination in English (VB001)
• Goals: Writing a thesis is frequently a long and arduous process and even more so when it has to be written in a language other than the author’s primary language. Therefore, this course is aimed at helping students who are in their last semester of studies to finish writing their theses. The course is separated into two tracks – a class track and an individual track. During the former, students attend six classes with the instructor and focus on the process of writing a thesis; the track will cover not only common grammar mistakes, but also the academic writing style or the mechanics of writing a thesis. The individual track has students write portions of their theses and then meet with the instructor on scheduled dates in order to receive feedback on their writing. There will be at least three individual sessions, each lasting 25-30 minutes. Students may be required to submit additional grammar and vocabulary exercises during both tracks. Students will have to pass an entrance exam in order to enroll into the course; this exam will be written during the first week of classes. Those with exceptionally good results will be offered the individual track only.
• Learning outcomes: The course gives students a thorough insight into the mechanics of academic writing in English. Students will learn to identify and correct frequent mistakes in academic writing made by both native and non-native speakers in English. In addition, students will also gain insight into common stylistic issues made in the field of computer science. Finally, the course should provide students with guidance and information important for a successful completion of a thesis in English language.
• Syllabus: I. Common grammatical mistakes, appropriate register (formal/informal language), II. Academic vocabulary, understanding the academic style of writing, III. writing paragraphs, IV. linking paragraphs together, V. understanding the organization of a thesis, VI. advanced issues in computer science writing

VV070 Seminar on Master's Thesis Writing

z 1/1 2 kr., jaro

• Mgr. Antonín Zita, M.A., Ph.D.
• Prerequisities: VB001
  The prerequisite for enrolling in the course is passing the examination in English (VB001)
• Goals: Writing a thesis is frequently a long and arduous process and even more so when it has to be written in a language other than the author’s primary language. Therefore, this course is aimed at helping students who are in their last semester of studies to finish writing their theses. The course is separated into two tracks – a class track and an individual track. During the former, students attend six classes with the instructor and focus on the process of writing a thesis; the track will cover not only common grammar mistakes, but also the academic writing style or the mechanics of writing a thesis. The individual track has students write portions of their theses and then meet with the instructor on scheduled dates in order to receive feedback on their writing. There will be at least three individual sessions, each lasting 25-30 minutes. Students may be required to submit additional grammar and vocabulary exercises during both tracks. Students will have to pass an entrance exam in order to enroll into the course; this exam will be written during the first week of classes. Those with exceptionally good results will be offered the individual track only.
• Learning outcomes: The course gives students a thorough insight into the mechanics of academic writing in English. Students will learn to identify and correct frequent mistakes in academic writing made by both native and non-native speakers in English. In addition, students will also gain insight into common stylistic issues made in the field of computer science. Finally, the course should provide students with guidance and information important for a successful completion of a thesis in English language.
• Syllabus: I. Common grammatical mistakes, appropriate register (formal/informal language), II. Academic vocabulary, understanding the academic style of writing, III. writing paragraphs, IV. linking paragraphs together, V. understanding the organization of a thesis, VI. advanced issues in computer science writing

VV071 Biochemistry for bioinformatics

zk 2/0 2 kr., podzim

• doc. RNDr. Irena Koutná, Ph.D.
• Prerequisities: none
• Goals: The objectives of the course Students will be familiar with the structure and function of biomolecules and their roles in the cell. The aim of the lectures is to provide sufficient knowledge that is necessary for a deeper study of biochemical and biological processes.The objectives of the course
• Learning outcomes: Background for study of molecular biology.
• Syllabus: 1. Introduction to the biochemistry. (Atoms and molecules. Amount of substance. Molecular weight. Chemical bond. Chemical reaction. Acids and bases. Buffers. Water. Solution. Concentration. Biogenic elements) 2. Amino acids and proteins (Peptide bond. Protein. Protein structure. Structural and chemical properties of amino acids in the protein structure. Protein function. Protein Detection Methods. Hemoproteins. Regulation of THE heme. Bile acids) 3. Enzymology I (Enzyme reactions. Kinetics and the thermodynamic of enzyme-catalyzed reaction. Inhibition of enzyme reactions) 4. Enzymology II (Classes of enzymes. Cofactors. Coenzymes. Vitamins and their functions) 5. Carbohydrates (Monosaccharides. Disaccharides and polysaccharides. Glycosidic bonds. Derivatives. Glycoproteins and proteoglycans) 6. Energy metabolism (Pentose cycle. Macroergic bonds. Anaerobic glycolysis and gluconeogenesis. Lactose and alcoholic fermentation) 7. Krebs cycle (citric acid cycle, acetyl coenzyme A . Energy Balance) 8. Respiration (Respiratory chain. Oxidative phosphorylation. ATP) 9. Photosynthesis (Structure and function of chlorophyll. The light and dark phase of photosynthesis) 10. Lipids (Structure and function. Biomembranes. Surfactants. Lipid Metabolism. Biosynthesis of fatty acids and cholesterol) 11. Nucleic acids. (Structure and function. Metabolism of nucleic acids) 12. Amino acids (Metabolism of amino acids. Secondary metabolites.)

VV072 Molecular biology for bioinformatics

zk 2/0 2 kr., jaro

• doc. RNDr. Irena Koutná, Ph.D. - Mgr. Pavel Šimara, Ph.D. - Mgr. Lenka Tesařová, Ph.D.
• Prerequisities: None
• Goals: The aim of this lecture is to provide the introduction into molecular biology and into general processes by which the cells express their genetic information. At the end of the course the student will be able to understand basic information about the genome structure and function, gene expression principles and the cell behaviour at the molecular level.
• Learning outcomes: Students understand the basic principles of biological processes at the level of molecules.
• Syllabus: 1. History of molecular biology. Nucleic acids and proteins (Structure and function of DNA, RNA and proteins; interaction of proteins with DNA) 2. Genome structure and genetic information (Structure of bacterial and eukaryotic genome, genome evolution, genetic code, transcription unit) 3. Genome replication, DNA repair and recombination (Replication of bacterial and eukaryotic genome, molecular basis of mutagenesis, DNA recombination and repair mechanisms) 4. Genome transcription (Transcription of bacterial and eukaryotic genome, post-transcriptional processing of RNA, mechanisms of RNA splicing) 5. Genome translation (Translation of bacterial and eukaryotic mRNA, the ribosome structure, post-translational processing) 6. Regulation of gene expression (Control of bacterial and eukaryotic genome expression, induction and repression, operon, transcription factors, posttranscriptional regulatory mechanisms) 7. Molecular mechanisms of signalling (Molecules involved in signalling pathways, receiving and processing of signals, communication between cells) 8. Molecular structure of eukaryotic cells (Molecular structure of the cell, transport of molecules within and outside the cell) 9. Cell cycle regulation (Molecular basis of cell cycle phases, regulation of cell growth and division) 10. Programmed cell death and molecular basis of acquired immunity (Immunoglobulins, BCR and TCR expression, development and activation of T- and B-cells) 11. Molecular basis of cancer (Basic characteristics of tumour cells, oncogenes, proto-oncogenes, tumour suppressors) 12. Methods of molecular biology and basic principles of gene engineering (Essential methods to study genome, transcriptome and proteome, genetic manipulations)

VV073 French for IT Business

z 2/0 2 kr., podzim

• Mgr. Kateřina Pánková
• Prerequisities: The course French for IT Business was created for IT students of the Masaryk University only. The level A2 in general French is required: a placement test will be organized during the first session of the term. Results will be communicated to students the following week. Max. capacity: 15 students. Placement test: 1h30, test of oral comprehension, reading comprehension, and written expression. If the number of enrolled students is lower than 6, the course will be run individually.
• Goals: The main goal of the course is to make students discover a pragmatic French language applied to the IT area which is regularly used in IT companies to work with French clients. The course lasts during the autumn term of the academic year 2018/2019 (12 sessions, 110 minutes each). Two types of courses: -11 Business French sessions applied to IT area moderated by a native French teacher from IBM CIC Brno (A placement test will be organized during the first session- Level A1 is required to enroll the course) -1 Main Frame workshop moderated by an IBM manager (in French and English):
• Learning outcomes: The student will be able to: -resolve a problem, a mishap, a conflict in French -present/defend an opinion/decision -give and receive instructions in French -explain/understand a process written in French language The student will acquire new social and linguistic skills: -in IT field -about working conditions in a French speaking company Courses output for IBM Mainframe workshop: Students will: -acquire knowledge in history of mainframe and its evolution during last 50 years (from IBM System/360 to IBM z14) -be able to use z/OS Basic concepts and vocabulary -be able to identify and define Mainframe jobs around the world (Application developer, Production control analyst, Operator, System Administrator, System Programmer, etc.) -Workshop: Practical showcase of logon and basic system checking

VV074 Laboratory of Theater Performances

z 0/0 1 kr., podzim

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: A course of stage speech and rhetoric, also useful for presenting and defending the results of scientific work. A course of specific knowledge and skills for the creation of a theater performance. Preparation for subject VV040 Theater Play.
• Learning outcomes: A student will be able to: Present her own or given speech in front of an audience; understand and explain the specifics of contemporary theater; to enumerate and elucidate the various components of the theatrical production; explain the ways of overhead approaches; compare theater management with management of scientific conferences.
• Syllabus: - Dramaturgy and focus of various theaters.
  - The specifics of the theatrical text compared to the text of the professional work.
  - Own dramatic text creation.
  - Methods of overhead approaches. K.S.Stanislavskij, J.A.Pitinský, A.Goldflam, P.Minařík and others.
  - Scenic music.
  - Lighting and sounding performance.
  - Stage design and costumes.
  - Theater Support Team - Inspiration, Help, Stage Design and Change During Performance, Stage Record.
  - Theater promotion and management.
  - Motion and gestures on stage, taking into account the presentation of your own scientific work at conferences.
  - Theater space and time.
  - Literary masterpieces of theatrical plays.
  - Psychosomatic exercises, the tension between the authenticity of the internal process and the external conditions. Improvisation etudes and exercises. Perception of a partner on the stage.

VV074 Laboratory of Theater Performances

z 0/0 1 kr., jaro

• doc. PhDr. Josef Prokeš, Ph.D.
• Goals: A course of stage speech and rhetoric, also useful for presenting and defending the results of scientific work. A course of specific knowledge and skills for the creation of a theater performance. Preparation for subject VV040 Theater Play.
• Learning outcomes: A student will be able to: Present her own or given speech in front of an audience; understand and explain the specifics of contemporary theater; to enumerate and elucidate the various components of the theatrical production; explain the ways of overhead approaches; compare theater management with management of scientific conferences.
• Syllabus: - Dramaturgy and focus of various theaters.
  - The specifics of the theatrical text compared to the text of the professional work.
  - Own dramatic text creation.
  - Methods of overhead approaches. K.S.Stanislavskij, J.A.Pitinský, A.Goldflam, P.Minařík and others.
  - Scenic music.
  - Lighting and sounding performance.
  - Stage design and costumes.
  - Theater Support Team - Inspiration, Help, Stage Design and Change During Performance, Stage Record.
  - Theater promotion and management.
  - Motion and gestures on stage, taking into account the presentation of your own scientific work at conferences.
  - Theater space and time.
  - Literary masterpieces of theatrical plays.
  - Psychosomatic exercises, the tension between the authenticity of the internal process and the external conditions. Improvisation etudes and exercises. Perception of a partner on the stage.

J012 Digital Forensics

zk 1/1 2 kr., podzim

• Goals: The aim of the course is to provide: Basic overview of the role and position of the Digital Forensics in the area of cybersecurity as well as in criminal investigation. Basic overview of the methods and procedures used in the process of the digital evidence identification and analysis.
• Learning outcomes: At the end of the course, the students will be able: to understand the specifics of Digital Forensics methods and processes, to assess quality and competency of outsourced digital forensic services, to implement elementary procedures of digital forensic analysis independently, especially to work as a digital forensics first responders.
• Syllabus: Digital Forensics in Cybersecurity; Digital Forensics in a criminal investigation; Digital traces and digital evidence, their properties Digital evidence documentation principles; Typical sources of the digital traces; Digital evidence handling; Digital evidence gathering and protection; Process of the digital forensics examination; Digital Forensics Laboratory - building and managing; Digital Forensics - certification and accreditation; Electronic Evidence in Czech and European context

BStaz Bachelor internship

z 0/1 25 kr., podzim

• RNDr. Jaroslav Ráček, Ph.D.
• Prerequisities: PB175 && PB007 && SOUHLAS
  
• Goals: The course goal is to let students experience the real world software development process, and provide them with knowledge and experience that is necessary for software developer/engineer work on a daily and weekly basis.
• Learning outcomes: After successful completion the student will - know from her own experience processes that are running at a background of the software development - be able to work with tools supporting real world development - understand activities that programmer of developer must deal with on a daily and weekly basis - get more deep knowledge and experience with a programming language used during the internship
• Syllabus: Expected time steps: - Selection of a company (place of the internship) from the list of offered stays or teacher's acceptance of the new proposed place and the workprogram based on the student's proposal - In total 50 workdays spent in accordance with the accepted workprogram - the usual structure is three days per week through the whole semester; the number of days can be increase if student is also working towards her bachelor thesis as a part of the internship - Running consultancies with the assigned supervisor from FI MU - Intermediate report describing internship progress in the middle of semester; the report must be accepted by the teacher/supervisor - Final report after the end of the internship; the report must be submitted and accepted before end of the exam period - Plenary presentation of the internship achievements before end of the exam period.

SBPrip Revisions for Bachelor State Exam

z 0/0 1 kr., jaro

• prof. RNDr. Jiří Barnat, Ph.D.
• Prerequisities: NOW ( SZB )
  
• Goals: The goal of this subject is to force students to commence preparation for final state exam in time. A secondary goal is let the student built an overview over all the topics studied so that she can realize the connections between the subjects.
• Learning outcomes: After graduation the student will have an overview of what she is expected to know for the final state exam.
• Syllabus: On the fly completion of questionares in IS.

SBAPR Bachelor Thesis

z 0/0 10 kr., podzim

• doc. RNDr. Pavel Matula, Ph.D.
• Goals: The course is designed as a final course encouraging students to write their diploma thesis meeting all the requirements placed on it. Completion of this course will ensure that the student submits bachelor thesis agreed by supervisor. The student should be ready for a successful defense of diploma thesis and aware of the requirements stated by a commission on defense.
• Learning outcomes: Students will create bachelor thesis and be prepared for its defense.
• Syllabus: Individual consultations during the work on the thesis.

SBAPR Bachelor Thesis

z 0/0 10 kr., jaro

• doc. RNDr. Pavel Matula, Ph.D.
• Goals: The course is designed as a final course encouraging students to write their diploma thesis meeting all the requirements placed on it. Completion of this course will ensure that the student submits bachelor thesis agreed by supervisor. The student should be ready for a successful defense of diploma thesis and aware of the requirements stated by a commission on defense.
• Learning outcomes: Students will create bachelor thesis and be prepared for its defense.
• Syllabus: Individual consultations during the work on the thesis.

SDIPR Diploma Thesis

z 0/0 20 kr., podzim

• doc. RNDr. Pavel Matula, Ph.D.
• Goals: The course is designed as a final course encouraging students to write their diploma thesis meeting all the requirements placed on it. Completion of this course will ensure that the student submits diploma thesis agreed by supervisor. The student should be ready for a successful defense of diploma thesis and aware of the requirements stated by a commission on defense.
• Learning outcomes: Students will create diploma thesis and be prepared for its defense.
• Syllabus: Individual consultations during the work on diploma thesis.

SDIPR Diploma Thesis

z 0/0 20 kr., jaro

• doc. RNDr. Pavel Matula, Ph.D.
• Goals: The course is designed as a final course encouraging students to write their diploma thesis meeting all the requirements placed on it. Completion of this course will ensure that the student submits diploma thesis agreed by supervisor. The student should be ready for a successful defense of diploma thesis and aware of the requirements stated by a commission on defense.
• Learning outcomes: Students will create diploma thesis and be prepared for its defense.
• Syllabus: Individual consultations during the work on diploma thesis.