FI MU Study Catalogue 2023/2024

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Digital Linguistics

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

The Joint Master Programme in Digital Linguistics will train highly qualified interdisciplinar profile combining knowledge and competencies from the field of computer science, information technology (IT), linguistics and humanities. Holders of the master’s degree in Digital Linguistics will have a broad set of applied IT skills and will be trained for programming, using and compiling language resources, using and adapting language technologies and autonomously conducting language data analyses. In addition, they will have a high level of competence in communication in at least two languages, will be able to recognise and adjust themselves to all types of written, spoken and digital texts as well as understand the principles of interlingual communication in all forms.

Holder of the master's degree in Digital Linguistics will be employable in various professional environments where technology-assisted language services are developed, offered or used.

Requirements for successful graduation

Compulsory subjects of the program

FF:CJBB105 Introduction in Corpus Linguistics – Lecture
MV013 Statistics for Computer Science
PA153 Natural Language Processing
FF:PLIN063 Alghoritmic Descript. of Morphology
SA400 Foreign Studies - Digital Linguistics
Foundations Pass at least 2 courses of the following list
FF:CJJ15 Czech Comparative Grammar
FF:PLIN041 History of Computational Linguistics
IB000 Mathematical Foundations of Computer Science
IV029 Introduction to Transparent Intensional Logic
Introduction to programming Pass at least 1 course of the following list
IB111 Foundations of Programming
IB113 Introduction to Programming and Algorithms
Application Oriented Electives I Pass at least 1 course of the following list
FF:PLIN045 Introduction to development of multiplatform applications
FF:PLIN055 Project from corpus and computational linguistics
PV061 Machine Translation
PV251 Visualization
Application Oriented Electives II Pass at least 1 course of the following list
FF:PLIN078 Quantitative analysis
PA107 Corpus Tools Project
PB138 Basics of web development and markup languages
PV211 Introduction to Information Retrieval
Methods and Tools I Pass at least 1 course of the following list
FF:PLIN032 Grammar and Corpus
FF:PLIN033 Algorithmic Description of Word Formation
PB095 Introduction to Speech Processing
IA161 Natural Language Processing in Practice
Methods and Tools II Pass at least 2 courses of the following list
FF:PLIN037 Semantic Computing
FF:PLIN077 Stylometry
IB047 Introduction to Corpus Linguistics and Computer Lexicography
PV004 UNIX
PV056 Machine Learning and Data Mining
PV080 Information security and cryptography
PA152 Efficient Use of Database Systems
Advanced Topics Pass at least 2 courses of the following list
FF:CJJ45 Topics in semantics
FF:PLIN065 Tools for theories
FF:PLIN068 Applied Machine Learning
FF:PLIN069 Applied Machine Learning Project
IV003 Algorithms and Data Structures II
PA128 Similarity Searching in Multimedia Data
PA154 Language Modeling
PA156 Dialogue Systems
SDIPR Diploma Thesis
SOBHA Defence of Thesis
SZMGR State Exam (MSc degree)

Study option: Study plan for local students

Compulsory subjects and other obligations of the study option

Internshipe abroad equal to 30 credits is expected in the third term.

Recommended course of study

Fall 2023 (1. term)
Spring 2024 (2. term)
Fall 2024 (3. term)
Spring 2025 (4. term)

Study option: Study plan for students from abroad

Students are expected to collect 30 credits within the term.

Compulsory subjects and other obligations of the study option

IA161 Natural Language Processing in Practice
FF:PLIN055 Project from corpus and computational linguistics
Selected Topics in Digital Linguistics Pass at least 3 courses of the following list
FF:CJBB184 Language Typology
FF:PLIN035 Computational Lexicography
FF:PLIN064 Introduction to Digital Humanities
FF:PLIN075 Linguistic Webinar
PA164 Machine learning and natural language processing
PA220 Database systems for data analytics
PV021 Neural Networks
PV061 Machine Translation
PV251 Visualization
IV111 Probability in Computer Science
Projects Obtain at least 4 credits by passing subjects of the following list
FF:PLIN034 Algorithmic Description of Syntax
FF:PLIN053 Mobile application programming project
PB106 Corpus Linguistic Project I
PV277 Programming Applications for Social Robots

Recommended course of study

Fall 2023 (1. term)
Spring 2024 (2. term)