Course of Study Computer Science (Study Cohort w15)

Sample course plan M  Master Computer Science (CSMS)
Specialisation Intelligence Engineering
Legend:
Core qualification CompulsorySpecialisation CompulsoryFocus CompulsoryThesis Compulsory
Core qualification Elective CompulsorySpecialisation Elective CompulsoryFocus Elective CompulsoryInterdisciplinary complement
LP
Semester 1FormHrs/wk
Semester 2FormHrs/wk
Semester 3FormHrs/wk
Semester 4FormHrs/wk
1
Algebraic Statistics for Computational Biology
Algebraic Statistics for Computational BiologyVL2
Algebraic Statistics for Computational BiologyUE2
Nonlinear Optimization
Nonlinear OptimizationVL3
Nonlinear OptimizationUE1
Research Project and Seminar
SeminarSE2
Master Thesis
2
3
4
5
6
7
Digital Image Analysis
Digital Image AnalysisVL4
Algebraic Methods in Information and Communication Technology
Algebraic Methods in Information and Communication TechnologyVL2
Algebraic Methods in Information and Communication TechnologyUE2
8
9
10
11
12
13
Intelligent Autonomous Agents and Cognitive Robotics
Intelligent Autonomous Agents and Cognitive RoboticsVL2
Intelligent Autonomous Agents and Cognitive RoboticsUE2
Operations Research
Operations ResearchVL2
Operations Research - SeminarSE2
14
15
16
17
18
19
Machine Learning and Data Mining
Machine Learning and Data MiningVL2
Machine Learning and Data MiningUE2
Intelligent Systems in Medicine
Intelligent Systems in MedicineVL2
Intelligent Systems in MedicineUE1
Intelligent Systems in MedicinePS2
20
21
22
23
24
25
Robotics and Navigation in Medicine
Robotics and Navigation in MedicineVL2
Robotics and Navigation in MedicineUE1
Robotics and Navigation in MedicinePS2
Applied Bioinformatics
Applied BioinformaticsVL3
Applied BioinformaticsUE3
26
27
28
29
30
Business & Management (from catalogue) - 6LP
Nontechnical Elective Complementary Courses for Master (from catalogue) - 6LP

The choice of courses from the catalogue is flexible (depends on the semestral work load), provided the necessary number of required credits is reached.