Course structure

The following course structure for the Master’s in Informatik / Computer Science (international) applies to students who have started their studies in or after the 2022/23 winter semester.

The structure of the degree course is as follows (in the event of a summer semester start, the order of the 1st and 2nd semesters will be reversed):

1. Semester

• Architecture of Information Systems (6 credits)
• Systems Analysis (6 credits)
• Artificial Intelligence (6 credits)
• Two required electives (6 credits each)

2. Semester

• Higher Mathematics (6 credits)
• Advanced Database Systems (6 credits)
• Scientific Seminar (6 credits)
• Two required electives (6 credits each)

3. Semester

• Master’s thesis (30 credits)

Students are free to decide upon the amount of modules taken per semester. But they have to consider, that (except for the thesis) all modules in the master degree courses are given in an annual base.

Three of the four required electives must be selected from computer science electives and one must be an interdisciplinary module. Computer science electives may be, for example: Computer Vision (AI), Planning and Scheduling  (AI), Network Security, Advanced Data Ming with R (AI), Simulation, Autonomous and mobile Robots (AI), Natural Language Processing (AI), E-Learning,  and others. Interdisciplinary electives include, for example, Project Management, Business Etiquette and Business Start-up. At least one of the three computer science electives must be chosen from the field of Artificial Intelligence (AI).

A detailed description of the course can be found in the module handbook under the Documents section.

One credit (synonymous with ECTS credit) is equivalent to 30 hours of work. 30 ECTS credits must be completed per semester. As a benchmark, a module worth six ECTS credits will keep you busy for one full working day every week during the semester. This approach is based on the EU-wide guidelines of the Bologna Process. 

All modules in the Master’s degree course therefore provide for a workload of eight hours per week. Nevertheless, the time spent in attendance at the university may vary from module to module. The attendance time is determined by the weekly teaching hours (SWS) of a particular class. 

Example: Artificial Intelligence, 1st semester. Four class hours are planned per week, so including preparation and follow-up work plus preparation for exams, a total of eight hours of work per week are to be planned for (also in part during the lecture-free period).