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

Introductory information / Instructions

Obtain at least 120 credits overall and pass the final state exam. Obtain 20 credits from SDIPR course and successfully defend Master's Thesis. Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form (unless explicitly stated otherwise). Fulfil requirements of at least one specialization.

Obligatory courses of the programme / Povinné předměty studijního programu

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Specialization
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 1Z
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 Specialization
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 Specialization
FI:IV111Probability in Computer Science V. Řehákzk 2/2/03+2 1P
FI:IA008Computational Logic A. Blumensathzk 2/2/03+2 2-
FI:PA153Natural Language Processing P. Rychlýzk 2/0/02+2 3-
FI:PA163Constraint Programming H. Rudovázk 2/1/03+2 1-
FI:PA228Machine Learning in Image Processing P. Matulazk 2/2/14+2 4-
FI:PA230Reinforcement Learning P. Novotnýzk 2/0/13+2 3-
30 credits

Optimizations and Numeric Computing

Pass at least 1 course of the following list

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Specialization
FI:PV027Optimization T. Brázdilzk 2/1/14+2 2-
FI:MA018Numerical Methods J. Zelinkazk 2/2/03+2 3-
11 credits

Applications of Machine Learning

Pass at least 1 course of the following list

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Specialization
FI:IA267Scheduling H. Rudovázk 2/02+2 4-
FI:PA212Advanced Search Techniques for Large Scale Data Analytics J. Sedmidubskýzk 2/0/02+2 4-
FI:PA128Similarity Searching in Multimedia Data P. Zezulazk 2/0/02+2 4-
FI:PV254Recommender Systems R. Pelánekk 1/1/02+1 4-
FI:PA164Machine Learning and Natural Language Processing V. Nováčekzk 2/1/03+2 3-
FI:IA168Algorithmic Game Theory T. Brázdilzk 2/0/13+2 3-
25 credits

Projects and Laboratory

Obtain at least 6 credits by passing courses of the following list

Code Name Guarantor Type of Completion Extent and Intensity Credits Term Specialization
FI:PA026Artificial Intelligence Project A. Horákk 0/2/02+1 4-
FI:IV125Lab Seminar – Formela A. Kučerak 0/2/02+1 3-
FI:PV253Lab Seminar – Data Intensive Systems and Applications (DISA) P. Zezulak 0/2/02+1 3-
FI:PV212Seminar on Machine Learning, Language Representation and Information Retrieval P. Sojkak 0/2/02+1 3-
12 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.