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Data Science

- Master´s programs

Department of Mathematics and Computer Science
Department of Education and Psychology
Takustr. 9
14195 Berlin

In order to get admitted to the master’s program applicants must fulfil the following admission criteria:

  • The applicant must hold a Bachelor’s degree in computer science or an equivalent degree with a total of 180 credit points (LP). These must include at least 20 LP in mathematics modules and at least 10 LP in computer science modules.

    The 20 LP in mathematics modules must contain at least 5 LP in linear algebra or calculus and at least 5 LP in probability theory or statistics. With regard to the required 10 LP in computer science modules, at least 5 LP must be in algorithms and at least 5 LP in a module that imparted knowledge of a higher programming language, e.g. C/ C++, Java or Python.
  • Any applicant who did not earn his or her university degree at an education institution where English is the language of instruction is required to prove English language skills at level C1 of the Common European Framework of Reference for Languages (CEFR).

More information is available in the now indefinite* Admission Statutes for the Master’s Degree Program in Data Science (in German).

*announcement of the de-termination (German only)
Students do not pay any tuition fees, the university only charges semester fees and contributions each semester.

This master's degree program imparts skills that are necessary in order to handle the advancing digitization of many areas of society and the physical and life sciences. This concerns, for example, the collection, processing, analysis and interpretation of large digital data sets. To this end, the master's degree program conveys the key aspects of modern data science, which is characterized by a blending of the central fields of mathematics, statistics, computer science and machine learning, taking application-related issues into account. With in-depth instruction in the relevant branches of mathematics, statistics and computer science as well as the areas of physical and life sciences that engage in quantitative work, this program provides the skills needed to recognize the relevant problems in data analysis, to develop and apply appropriate mathematical or computer science solutions and to correctly interpret the results within the specific application context.

Possibility of specialization in the profile areas of Data Science in Life Sciences and Data Science Technologies.

1st Semester Admissions
Restricted admission
Admission for Higher Semesters
Restricted admission (for 3rd semester for winter semester, for 2nd and 4th semester for summer semester)
Program Start
Winter semester
Master of Science (M.Sc.)
4 semesters

The program comprises a foundation 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 the specializations

  • Data Sciences in Life Sciences
  • Data Science Technologies


Module list

Foundation area (mandatory modules)

Module  Statistics for Data Science
Module  Machine Learning for Data Science
Module  Programming for Data Science
Module  Introduction to Profile Areas

Selected elective modules of the profile areas

Module  Ethical Foundations of Data Science
Module  Data Science in the Life Sciences
Module  Selected topics in Data Science Technologies
Module  Data Science Data Bases
Module  Artificial Intelligence
Module Machine Learning in Bioinformatics
Module Current Research Topics of Data Science in Life Sciences
Module Softwareproject Data Science

Graduates are prepared to hold positions of leadership in subject-specific terms in a wide range of different fields of activity relating to collection, management, preparation, analysis and interpretation of digital data. These include, for example, the areas of Internet economy, health or Industry 4.0 or corresponding facilities and institutions in the industrial, research and administrative sectors. A further academic qualification can also be acquired within the framework of a PhD.