In this master’s course, skills are imparted that are required to deal with the advancing digitization of many areas of society and the natural sciences. This applies, for example, to the acquisition, processing, analysis and interpretation of large digital data sets. The master’s course conveys the central aspects of modern data science, which is characterized by the amalgamation of the central fields of mathematics, statistics, computer science and machine learning, taking application-related issues into account. Through in-depth training in the corresponding sub-areas of mathematics, statistics and computer science, as well as in the relevant quantitative application fields of natural, social,


The course is divided into a basic area with the modules

  • Statistics for Data Science
  • Machine learning for data science
  • Programming for Data Science
  • Introduction to Profile Areas

and a profile area with specializations

  • Data Science in the Social Sciences
  • Data Sciences in the Life Sciences
  • Data Science Technologies

The course and examination regulations regulate the exact structure and course of the course. It describes the content, type and requirements of the compulsory and elective modules.

The master's thesis with 30 CP should show that the students are able to work on a research task independently using scientific methods and to present the results in writing and orally. After successfully completing the study program, the university degree Master of Science (M.Sc.) is awarded.

Modules of the course

Compulsory modules of the basic area

module  Statistics for Data Science
module  Machine learning for data science
module  Programming for Data Science
module  Introduction to Profile Areas

Selection of elective modules in the profile area

module  Ethical Foundations of Data Science
module  Data Science in the Social Sciences
module  Data Science in the Life Sciences
module  Selected topics of data science technologies
module  Database systems data science
module  Artificial intelligence
module  Cognitive Neuroscience for Data Science
module Natural Language Processing
module Data Science software project



The graduates are prepared for a professional management position in a wide variety of fields of activity that go hand in hand with the collection, administration, processing, analysis and interpretation of digital data. These include, for example, the areas of internet economy, health or Industry 4.0 or corresponding facilities in industry, research and administration.



To be admitted to the master’s degree, applicants must demonstrate the following requirements:

  • Completion of a university degree with a total of 180 credit points (CP) with a study share of at least 20 CP in mathematics modules and at least 10 CP in computer science modules.

    These 20 CP in math modules must contain at least 5 CP in the areas of linear algebra or analysis and at least 5 CP in the areas of probability theory or statistics. With regard to the required 10 LP computer science modules, at least 5 LP in the area of ??algorithms and at least 5 LP in a module must be proven by acquiring knowledge of a higher programming language, e.g. C / C ++, Java or Python.
  • Applicants who did not obtain their university degree at an educational establishment in which English is the language of instruction must provide evidence of English language skills to the extent of level B2 of the Common European Framework of Reference for Languages ??(GER).

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