The master's degree in Data Science provides excellent expertise in the areas of machine learning / big data analytics in order to be able to implement this in practice in the company.

Data science users are companies with intelligent systems / machines that process large data streams to make predictions. This includes partner companies in the field of logistics, market research, retail, health and platform operators for machine intelligence. The course covers the entire spectrum for data products, including modeling, data cleansing, practical experience with diverse data sets and testing of production-ready solutions.

The master’s program comprises four semesters and five training blocks:

  1. Data science relevant fundamentals of mathematics and statistics
  2. Basics of computer science for data science
  3. Ethics and economic aspects for data science
  4. Machine learning
  5. Application-oriented projects and courses for data science

In the last semester, the master's thesis has to be written, which scientifically covers an innovative sub-area or realizes new application-oriented solutions for start-ups or companies.


Due to the extensive research work of the Data Science department, there are diverse relationships with many dozen innovative companies that also provide us with specific questions and data. This ensures that the course content can be conveyed in tune with the times.

At the same time, initially known reference data sets (Kaggle, Government Data, FiveThirtyEight, etc.) are analyzed in order to analyze practical questions around the world.


The data science group is one of the strongest research groups at universities in Berlin. Current high-publication research projects such as FashionBrain (H2020), ExCELL (BMWi), Smart Data Web (BMWi), MACSS (BMWi), Berlin Big Data Center (BMBF), Smart Learning (BMBF), Brain-Bots, OCIDA (IFAF), etc. . are all positioned in the field of data science / machine learning and ensure a suitable research connection.


1st semester of the curriculum

module Module name SU SWS Ü SWS LP P / WP FB
M01 Mathematical models 4th   5 P. II
M02 Advanced software technology 2 1 5 P. VI
M03 Statistical Computing 2 1 5 P. II
M04 Practice of data science programming 2 2 5 P. VI
M05 Computer science for big data 2 1 5 P. VI
M06 Business intelligence and responsibility 4th   5 P. VI

2nd semester of the curriculum

module Module name SU SWS Ü SWS LP P / WP FB
M07 Data visualization 2 2 6th P. II
M08 Regression 2 2 6th P. II
M09 Machine learning I 2 2 6th P. II
M10 Application 1: Data Science Workflow / Applications 4th   7th P. VI, II
M11 Elective module I   4th 5 WP VI
  Elective modules          
WP01 Text mining and NLP   4th 5 WP VI
WP02 ML as a service and analytic engines   4th 5 WP VI

3rd semester of the curriculum

module Module name SU SWS Ü SWS LP P / WP FB
M12 Machine Learning II 2 2 5 P. II
M13 Application 2: Urban Technologies 4th   5 P. VI
M14 Application 3: Enterprise Data Science 4th   5 P. VI
M15 Studium Generale I 2   2.5 WP I.
M16 Studium Generale II   2 2.5 WP I.
M17 Business value 4th   5 P. I.
M18 Elective module II   4th 5 WP II or VI
  Elective modules          
WP03 Deep learning   4th 5 WP VI
WP04 Learning from Images   4th 5 WP VI
WP05 Sampling and design of experiments   4th 5 WP II
WP06 Learning Optimization   4th 5 WP II

4. Semester of the curriculum

module Module name SU SWS Ü SWS LP P / WP FB
M19 final exam       P.  
M19.1 Master thesis     25th P.  
M19.2 Oral exam     5 P.


  • At least (I) English language level B2
  • At least (II) 20 ECTS in mathematics / statistics, e.g. B. Analysis, linear algebra, numerical mathematics, probability theory, data modeling
  • At least (III) 25 ECTS in computer science, e.g. B. Programming, databases, distributed systems, application programming


In Berlin, Germany and around the world, data scientists are among the most sought-after professional group with the highest salary. All partner companies also support the course because graduates are urgently needed.

According to all leading research institutes, the market for intelligent systems will grow faster than any other market. Since intelligent systems have to be used in all industries, data scientists are in demand across all industries.


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