FI ZPJ Natural language processing
Name in Czech: Natural language processing
master's full-time specialized, language of instruction: English English
Included in the programme: FI N-UIZD_A Artificial intelligence and data processing

Study-related information

  • Parts of the final state examination and its content
    The state master's examination consists of a thesis defence and an oral examination. The entire state examination lasts 1 hour (approximately 30 minutes defence, 30 minutes examination). The student has 15 minutes to present his/her thesis, and another 15 minutes are devoted to the analysis of the reports and discussion. During the examination, the student answers unprepared questions, typically a debate of two to three questions.

    In the case of negative opinions on the thesis, the student may waive the defense, accept the "fail" grade and proceed directly to the examination. In the case of a failed defence, it is not possible to withdraw from the examination.

    The reason for failing the Master's State Examination is:

    The student fails to explain (even intuitively) any of the concepts explicitly stated in the question wording.
    The student is able to formulate definitions of the concepts but is unable to apply them practically even with an elementary example.
    The student knows the concepts explicitly stated in the question wording, but all only at a superficial level, unable to respond to follow-up questions.
    Ignorance from one question (i.e., F-level knowledge) cannot be balanced by brilliant knowledge from the other questions.

    The language in which the exam is administered depends on the program. English programs are tested in English, while the other programs are tested in Czech (or Slovak) as the primary language; however, English may be tested by mutual agreement. The thesis defense is expected in the language in which the thesis is written.
  • Suggestion of theses topics and the topics of defended theses
    Examples of thesis topics:
    1) Global Calendar: https://is.muni.cz/auth/th/374516/fi_m/
    2) Methods of dimensionality reduction of vector spaces: https://is.muni.cz/auth/th/374346/fi_m/
    3) Fusion of separation methods: https://is.muni.cz/auth/th/255821/fi_m/
    4) Deep neural networks for multimedia processing: https://is.muni.cz/auth/th/430614/fi_m/
    5) Morphosyntactic analysis of Slovak: https://is.muni.cz/auth/th/359226/fi_m/

Recommended progress through the study plan

Obligatory courses of the programme / Povinné předměty studijního programu

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Profile Cat.
FI:MA012Statistics II O. Pokorazk 2/2/03+2 1P
FI:IV126Fundamentals of Artificial Intelligence H. Rudovázk 2/0/13+2 1Z
FI:PA234Infrastuctural and Cloud Systems T. Rebokzk 2/2/03+2 2-
FI:PA152Efficient Use of Database Systems V. Dohnalzk 2/0/13+2 2Z
FI:PV021Neural Networks T. Brázdilzk 2/0/24+2 3Z
FI:PV056Machine Learning and Data Mining J. Sedmidubskýzk 2/0/13+2 2Z
FI:PV211Introduction to Information Retrieval P. Sojkazk 2/1/03+2 2Z
FI:PV251Visualization B. Kozlíkovázk 2/1/03+2 1Z
FI:SOBHADefence of Thesis D. SvobodaSZk 0/0/0- 4-
FI:SZMGRState Exam (MSc degree) D. SvobodaSZk 0/0/0- 4-
41 credits

Master's Thesis / Diplomová práce

Obligation to obtain 20 credits from the SDIPR course.

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Profile Cat.
FI:SDIPRDiploma Thesis D. Svobodaz 0/0/020 4-
20 credits

Obligatory courses for specialization / Povinné předměty specializace

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Profile Cat.
FI:IA161Natural Language Processing in Practice A. Horákk 1/1/02+1 3Z
FI:IV111Probability in Computer Science V. Řehákzk 2/2/03+2 1P
FI:PA153Natural Language Processing P. Rychlýzk 2/0/02+2 1Z
FI:PA154Language Modeling P. Rychlýzk 2/0/02+2 2P
FI:PA164Machine learning and natural language processing V. Nováčekzk 2/1/03+2 1-
FI:PV061Machine Translation P. Rychlýzk 2/0/02+2 3-
FI:IA008Computational Logic A. Blumensathzk 2/2/03+2 2-
30 credits

Extending theoretical subjects

Pass at least 2 courses of the following list

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Profile Cat.
FI:MA010Graph Theory D. Kráľzk 2/1/03+2 3-
FI:MA015Graph Algorithms J. Obdržálekzk 2/1/03+2 3-
FI:MA018Numerical Methods J. Zelinkazk 2/2/03+2 3-
PřF:M7130Computational geometry J. Slovákzk 2/0/02+2 3-
19 credits

Seminar or Project

Pass at least 1 course of the following list

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Profile Cat.
FI:PV173Natural Language Processing Seminar A. Horákk 0/2/02+1 4-
FI:PV277Programming Applications for Social Robots A. Horákk 0/1/01+1 3-
FI:PB106Corpus Linguistic Project I P. Rychlýz 0/2/02 3-
FI:PA107Corpus Tools Project P. Rychlýz 0/2/02 4-
9 credits

Free credits / Volné kredity

Complete additional courses so that the total credit gain is at least 120 credits for the entire study of this degree programme.