- Degree
- Master of Science
- Course location
- Magdeburg
- Teaching language
- • English
• German
- Languages
- English, German
The degree can be studied in both languages, i.e. a student who is proficient in only one of these two languages can study in the degree programme. Students are not expected to be proficient in both languages.
- Full-time / part-time
- • full-time
- Programme duration
- 4 semesters
- Beginning
- Winter and summer semester
- Additional information on beginning, duration and mode of study
- There is an introductory week/event before the actual lecture period starts – make sure to be here in time to attend it.
Additional information for incoming students can be found here:
https://www.inf.ovgu.de/inf/en/Study/Being+a+student/Incoming.html (https://www.inf.ovgu.de/inf/en/Study/Being+a+student/Incoming.html)
- Application deadline
- Winter semester: 15 May (international applicants)
Summer semester: 15 November (international applicants)
Dates may differ for the current semester; please check the programme website.
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- The MDKE Data Science Master's programme delivers in-depth knowledge and competences in data science, one of the most promising career areas for ambitious Bachelor's graduates. Its subject area is "engineering" for data and for knowledge, aiming to turn passive data into exploitable knowledge.
It focuses on the representation, management, and understanding of data and knowledge assets. It encompasses technologies for the design and development of advanced databases, knowledge bases and expert systems, methods for the extraction of models and patterns from conventional data, texts and multimedia, and modelling instruments for the representation and updating of extracted knowledge. The MDKE programme can be studied in German or English, and is thus open to students who are proficient in either of the two languages.
MDKE spans application areas ranging from business intelligence and industry to life sciences, biotechnology, and security. The management and analysis of data is essential; the maintenance and understanding of knowledge assets are of major importance in business venues, in governmental authorities, and in non-profit organisations.