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A group consists of courses that have the same role in a study plan. A group thus facilitates the requirement on credits to be acquired in a prescribed structure for a study plan. Hence, a student just cannot accumulate the required amount of credits required by the study plan; s/he must meet the requirements of each group of courses of a given study plan.
       Each student has to complete either at least a prescribed minimum (amount of) credits or to successfully complete a prescribed minimum (amount of) courses for a given group.
If a group has defined a minimum amount of credits = total amount of credits that can be obtained from the group, the student must successfully complete all the courses of the group. Such a group of courses has its role marked as 'compulsory'. If a group has defined a minimum amount of credits < total amount of credits obtainable from the group, such a situation is referred to as a group with an obligation to choose and complete at least the minimally set amount of credits. Similarly for courses.
If a group has defined a minimum amount of credits = 0 and a minimum number of courses = 0 at the same time, then the courses in the given group are elective.
Ifa a group has defined a minimum amount of credits < maximum amount of credits < total amount of credits obtainable from the group, then credits earned earned above the minimum amount of credits are seen as elective and credits above the maximum amount of credits from a given group do not count.
For ease of reference, each group has a role of the courses in the given study plan assigned next to its name.
The list is sorted alphabetically by the Department code and Course title.
Group: Compulsory Courses of Master Branch Knowledge Engineering, in Czech, Version 2018
Min. credits: 35   Credits total: 35   Min. courses: 7 Role: PO - compulsory courses in the field
Course Course title Extend of
teaching
Comple-
tion
Seme-
ster
Recomm.
sem.
Cre-
dits
Instruc-
tor
Cat.
MI-UMI Artificial intelligence 2P+1C Z,ZK Z 1 5 18105
MI-PDD.16 Data Preprocessing 2P+1C Z,ZK Z 1 5 18105
MI-DDW.16 Web Data Mining 2P+1C Z,ZK L 2 5 18102
MI-MVI.16 Computational Intelligence Methods 2P+1C Z,ZK Z 2 5 18105
MI-ADM.16 Data Mining Algorithms 2P+1C Z,ZK L 2 5 18105
MI-PDB.16 Advanced Database Systems 2P+1C Z,ZK Z 3 5 18102
MI-EDW.16 Enterprise Data Warehouse Systems 2P+1C Z,ZK L 3 5 18105


Page updated 14. 12. 2024, semester: Z/2019-20, L/2021-2, L/2019-20, Z/2024-5, Z/2023-4, Z,L/2020-1, L/2024-5, Z/2021-2, L/2022-3, L/2023-4, Z/2022-3, Send comments to the content presented here toAdministrator of study plans Design and implementation: J. Novák, I. Halaška