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Data Science

- Master´s programs

Department of Mathematics and Computer Science
Department of Education and Psychology
Prof. Katinka Wolter (Computer Science); Prof. Tim Conrad (Mathematics, Bioinformatics); Prof. Dirk Ostwald (Psychology, Computational Cognitive Neuroscience)
Takustr. 9
14195 Berlin
Prof. Wolter: +49 (0)30 838 75146; Prof. Conrad: +49 (0)30 838 51445; Prof. Ostwald: +49 (0)30 838 56860
(030) 838-546 56

For admittance to the master’s program applicants need to fulfil the following admission requirements:

  • The applicant must have a degree with a total of 180 credit points (LP) with a study share of at least 20 LP in mathematics modules and at least 10 LP in computer science modules.

    These 20 LP in mathematics modules must contain at least 5 LP in the areas of linear algebra or analysis and at least 5 LP in the areas of probability theory or statistics. With regard to the required 10 LP in computer science modules, at least 5 LP must be in the area of 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 B2 of the Common European Framework of Reference for Languages (CEFR).

Admission is limited. For more information about admission requirements see the admission regulations (only in German).

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 education in the corresponding branches of mathematics, statistics and computer science as well as in the relevant application fields of the physical and life sciences, social sciences and humanities that engage in quantitative work, this program imparts the skills needed to recognize the relevant problems in data analysis, develop and apply appropriate mathematical or computer science solutions and correctly interpret the results within the specific application context.

Possibility of specialization in the profile areas Data Science in the Social Sciences, Data Science in the 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)
Application and Registration Period
Only for 1st semester: April 15 – May 31 (for winter semester), only for higher semesters: July 1 - August 15 (for winter semester), and January 1 - February 15 (for summer semester)
Program Start
Winter semester
Master of Science (M.Sc.)
4 semesters

The program comprises a fundamental 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 Science in the Social Sciences
  • Data Sciences in the Life Sciences
  • Data Science Technologies


Module list
Fundamental area (Mandatory modules)

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

 Selected elective modules of the profile areas

  • Ethical Foundations of Data Science 
  • Data Science in the Social Sciences 
  • Data Science in the Life Sciences 
  • Selected topics in Data Science Technologies 
  • Data Science Data Bases 
  • Artificial Intelligence
  • Cognitive Neuroscience for Data Science
  • Natural Language Processing
  • 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 doctor-ate.