FACULTY OF

COMPUTER SCIENCE

   NO

• Modules are being added each semester: If you look now, you do not necessarily see all modules of the next semester.
• Seminars and individual projects are not listed (see later Q)

   NO

• Modules must fit thematically
• Some modules that fit thematically are not permitted, e.g. early bachelor modules
• Get permission before enrolling
• Never enroll to a module for which you have no prior approval ! You risk that you cannot have the credits counted.

   Yes, you can use either the Erasmus exchange programme or one of our bilateral exchange programmes. BEWARE: Restrictions apply!

1. 1. Prepare a learning agreement between OVGU and the target university BEFORE you leave.
      • Choose the modules carefully.
      • Map the modules to the thematic areas.
      • Make sure that the Credit Points agree.
   2. Get the learning agreement approved by your Studies Advisor and have it filed in the Examinations Office
   3. Get the learning agreement approved by the target university
   4. Report any changes to the learning agreement, as soon as you encounter them, and have the changes approved (see Step 2)

• no explicit limit
• must fit to thematic area

• You can do an internship if you want, 
• but it is not part of your studies!
• IMPLICATIONS: 
1. 1. 1. The company may ask for a verification that an internship is part of your studies.
      2. If you need a visum to do the internship, the visa-issuing authority will ask for a verification that an internship is part of your studies.
• You cannot get such a verification. Under no circumstances.
• We can certify that the specific internship is good for your further study, but IF AND ONLY IF: 
  • The internship fits excellently into one area of your studies, and in this area you still must make ECTS. 
• A specific internship may be good for your further study

• Modules in Master Data Science MDKE:
  • Eligible courses that fit to the thematic areas of Master Data Science MDKE
  • 6 ECTS per course (5 or less ECTS possible) 
• Course Types offered in the FIN:
  • Vorlesung mit Übung
  • Scientific Seminar
  • Team Project
  • Individual Project
  • ...

   At least one!

• no explicit limit
• must be declared as FIN Team Projects and you must have still empty space under "Applied Data Science"

There’s no formal requirement to take all fundamental courses in the first term. However, these courses are meant to provide a basis for the remainder of the programs and, it is hence best to take them as early as possible. Also note, you don’t have to take a course (e.g. Introduction to Computer Graphics) that you took in a previous program.

There is no internship in the program and you won’t get credit for it. However, the summer break between the first and second term is a good opportunity for an internship. Many students also work part-time next to their studies in a computer science related job.

• DO NOT choose seminars before attending PPSW, unless you have had a scientific seminar in your previous studies
• DO NOT choose courses that expect background you do not have
• DO NOT assume that you can acquire background knowledge you do not have in parallel to a course that requires this background knowledge
• DO consult the interview video with the teacher, before enrolling to the course

• DO NOT use LSF to map courses to areas; use exclusively the Module Hand Book
• DO map team projects exclusively in the area 'Applied Data Science' -- even if the Module Hand Book seems to permit something different !!