Data and Knowledge Engineering
The Master DKE delivers in-depth knowledge and competences in Data Science, one of the most promising career areas for ambitious computer scientists. Its subject area is "Engineering" for Data and for Knowledge, aiming to turn passive data into exploitable knowledge:
It focusses 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, modelling instruments for the representation and updating of extracted knowledge. The Master DKE can be studied on German or English and is thus open to students mastering either of the two languages.
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. The management and analysis of data, the maintenance and understanding of knowledge assets are of major importance in business venues, in governmental authorities and in non-profit organisations. In the Master DKE, we prepare our students for a career as:
- Knowledge engineers in large institutions like banks, medical centres, joint ventures and holdings but also in small and medium size enterprises - Project managers for interdisciplinary projects that demand data-intensive solutions
- IT-consultants, specialized in the design and development of knowledge-intensive scenaria; application areas include e-business, biotechnology and customer relationship management
- Researchers on information systems, intelligent systems and their many application areas
- The Master DKE also provides the foundations for further studies towards a PhD degree.
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A summary of the structure of the degree programm can be found in the DKE structure overview.
At a glance
|Degree||Master of Science (M.Sc.)|
|Standard period of study||4 Semester|
|Start of studying||winter term or summer term|
|Conditions of admission||
According to our statutes, a successful applicant must:
(1) have graduated from a degree in Computer Science or in a CS-close discipline containing at least 10 CS courses (60 ECTS credits) and additional course in Databases; up to 4 courses (20 ECTS credits) on applied statistics are also considered as relevant,
(2) have a good grade/mark in that degree and
(3) master either the English or the German language.
Criterion (3) requires a language certificate.
Thresholds for criterira (2) and (3), links to submission instructions and submission deadlines can be found under
For criterion (2), the treshold is 2,500 in the German System.
For criterion (3), the threshold is CEFR C1. The mapping of CEFR C1 to the certificates acceptable by our University is described under
|More information abut applications|