Obligatory and Elective Courses of the LCT Program in Prague

Name of the qualification: magistr
Title conferred: Mgr. (MSc. equivalent)
Study programme/Subject of qualification: Informatics/Computational Linguistics

Each student has to pass all obligatory courses (5) at the Charles University (or their equivalents at a partner university - subject to approval) and the Final State Exam in particular.

Each student has to gain at least 42 ECTS from the list of elective courses at the Charles University (or their equivalents at a partner university - subject to approval).

More Detailed Information:

Diploma Theses

State Exams (Oral Part) - students are examined from five areas:

  • from two obligatory areas covering the theoretical foundations of computer science (description of the areas can be found here):
    • complexity and computability, and
    • data structures;
  • from the obligatory area for the study branch Computational Linguistics (description of the area can be found here):
    • fundamentals of natural language processing
  • from two areas specific to the student's specialization within the study branch Computational Linguistics - the student will select these two examination areas when registering for the final exam; description of the areas can be found here.

Tuition Fee

The local tution fee for LCT students is covered from the LCT program - this fee covers one year of study at the Charles University.

The student obliges him/herself to complete the LCT Program requirements within the deadline specified in the academic calendar (typically the end of September). If the student fails to meet this deadline (s)he can ask for a program extenssion.

In case of the extension, the Charles University local fee will be demanded from the student according to the local regulations specified at the faculty webpage. If the student has finished his/her coursework and (s)he is just workoing on his/her master thesis, (s)he can ask for 80% reduction of the local fee (in written).

 

 

The Coverage of LT Modules in Prague

The following table summarizes main courses covering LT modules (may be subject of marginal changes – please check in the Student Information System).

Module Code Name ECTS Type Semester
Methodologies (LT-M1) NPFL067 Statistical Methods in Natural Language Processing I (obligatory) (3/6) 3 C+Ex winter
NPFL063 Introduction to General Linguistics (obligatory) 5 C+Ex winter
NPFL070 Language Data Resources 5 MC summer
NPFL038 Fundamentals of Speech Recognition and Generation 6 C+Ex winter
NPFL006 Introduction to Formal Linguistics 3 Ex winter
Computational Syntax and Morphology (LT-M2) NPFL067 Statistical Methods in Natural Language Processing I (obligatory) (3/6) 3 (see above)
NPFL094 Morphological and Syntactic Analysis 3 MC winter
NPFL096 Computational Morphology 4 Ex summer
NPFL093 NLP Applications (3/5) 3 MC summer
NPFL083 Linguistic Theory and Grammar Formalisms 6 C+Ex summer
NPFL012 Introduction to Computer Linguistics 3 Ex winter
Computational Semantics, Pragmatics and Discourse (LT-M3) NPFL082 Information Structure of Sentence and Discourse Structure 3 Ex summer
NPFL075 Prague Dependency Treebank (3/6) 3 C+Ex summer
NPFL093 NLP Applications (2/5) 2 (see above)
NPFL088 Lexical Analysis of Natural Language 3 C summer
Specialized (LT-M4) NPFL068 Statistical Methods in Natural Language Processing II 6 C+Ex summer
NPFL015 Methods of Automated Translation 3 C winter
NPFL087 Statistical Machine Translation 6 C+Ex summer
NPFL075 Prague Dependency Treebank (3/6) 3 (see above)
NPFL079 Algorithms in Speech Recognition 6 C+Ex summer

The Coverage of CS Modules in Prague

The following table summarizes main courses covering CS modules.

Module Code Name ECTS Type Semester
Data Structures, Data Organization and Processing (CS-M1) NTIN066 Data Structures I (obligatory) 5 C+Ex winter
NPFL092 NLP Technology (obligatory) 5 MC winter
NPFL103 Information Retrieval 6 C+Ex winter
Logic, Computability and Complexity (CS-M2) NTIN090 Introduction to Complexity and Computability Theory (obligatory) 5 C+Ex winter
NPFL081 Practical Fundamentals of Probability and Statistics for Computer Linguistics 3 C winter
Formal Languages and Algorithms (CS-M3) NTIN071 Automata and Grammars 6 C+Ex summer
NPFL054 Introduction to Machine Learning (3/6) 3 C+Ex winter        
NOPT042 Constraint Programming 6 C+Ex winter
Advanced (CS-M4) NPFL054 Introduction to Machine Learning (3/6) 3 (see above)
NPFL104 Machine Learning Methods 5 C+Ex summer
NPFL095 Modern Methods in CL 3 C winter
NPFL099 Statistical Dialog Systems 5 C+Ex summer
NAIL069 Artificial Intelligence I 5 C+Ex winter
NAIL070 Artificial Intelligence II 3 Ex summer

Note that there is a great number of other CS courses taught in Czech. Depending on student's interest, English lessons may be arranged. Please, contact us.

 

Grading scheme

seminar C = credited (i.e., requirements of a course are fulfilled ) Czech abbrev. Z

MC = requirement with assessment
     1 = excellent
     2 = very good
     3 = good
     4 = fail

Czech abbrev. KZ
lecture

Ex = exam
     1 = excellent
     2 = very good
     3 = good
     4 = fail

Czech abbrev. Zk

Grading equivalent table recommended by the European Office can be found here.