Information

The degree is organized across five thematic areas; students attend modules and acquire credit points through courses, team projects and seminars in all areas:

Underpinnings: Basics of data mining, database processing, data/image/multimedia engineering
Models: Knowledge representation, knowledge modeling, knowledge processing
Methods I: Knowledge discovery, artificial intelligence, machine learning
Methods II: Information processing and retrieval
Applications: Application of DKE, including business applications, medical applications, engineering applications, core CS applications (e.g. security, image understanding) DKE spans application areas ranging from business intelligence and market watches to life sciences, biotechnology and security. It builds upon advances in networked services, people and agent communication, in decision support, information systems and management.

List of courses

The courses scheduled in the current term can be found in the information system LSF of the university. In the following, we provide some links that create a lists/plans of courses offered this term for your convenience:

Please remark that some courses might be given in German or English depending on the needs of the students that are attending the course. Check back with the lecturer in the beginning of the term.