Sample course plan A Master Computer Science in Engineering (IIWMS) Dual study program
Specialisation I. Computer Science, Specialisation II. Engineering Science, Specialisation III. Mathematics, Specialisation IV. Subject Specific Focus
Legend: |
Core Qualification Compulsory | Specialisation Compulsory | Focus Compulsory | Thesis Compulsory |
Core Qualification Elective Compulsory | Specialisation Elective Compulsory | Focus Elective Compulsory | Interdisciplinary complement |
LP | | | | |
1 | | | | |
Practical module 1 (dual study program, Master's degree) | Practical term 1 | | 0 |
| | | | |
Practical module 2 (dual study program, Master's degree) | Practical term 2 | | 0 |
| | | | |
Research Project | Research Project IIW | PK | 8 |
| | | | |
Master thesis (dual study program) | | | |
|
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 | | | | |
Software Verification | Software Verification | VL | 2 | Software Verification | GÜ | 2 |
| | | | |
Algorithmic Game Theory | Algorithmic game theory | VL | 2 | Algorithmic game theory | HÜ | 2 |
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12 |
13 | | | | |
Practical module 3 (dual study program, Master's degree) | Practical term 3 | | 0 |
|
14 |
15 |
16 |
17 | | | | |
Mathematical Image Processing | Mathematical Image Processing | VL | 3 | Mathematical Image Processing | GÜ | 1 |
| | | | |
Advanced Internet Computing | Advanced Internet Computing | VL | 2 | Advanced Internet Computing | PBL | 2 |
|
18 |
19 |
20 |
21 |
22 |
23 | | | | | |
Information Theory and Coding | Information Theory and Coding | VL | 3 | Information Theory and Coding | HÜ | 2 |
| | | | |
Advanced Machine Learning | Advanced Machine Learning | VL | 2 | Advanced Machine Learning | GÜ | 2 |
|
24 | |
25 | |
26 | |
27 | |
28 | |
29 | | | | | |
Machine Learning in Electrical Engineering and Information Technology | General Introduction Machine Learning | VL | 1 | Machine Learning in Wireless Communications | VL | 1 | Machine Learning in Electromagnetic Compatibility Engineering | VL | 1 | Machine Learning in High-Frequency Technology and Radar | VL | 1 | Machine Learning Applications in Electric Power Systems | VL | 1 |
| |
30 | | |
31 | | | |
32 | | | |
33 | | | |
34 | | | |
| Business & Management (from catalogue) - 6LP |
| Linking theory and practice (dual study program, Master's degree) (from catalogue) - 6LP |
| Technical Complementary Course II for Computational Science and Engineering - 12LP |
| Technical Complementary Course I for Computational Science and Engineering - 12LP |
The choice of courses from the catalogue is flexible (depends on the semestral work load), provided the necessary number of required credits is reached.