Note: The conversion ratio of semester hours per week (SWS) on ECTS is about 1.5. A module with a workload of 6 ECTS credits corresponds to approximately 4 hours per week for example. Also, several courses / modules can be combined to cover a corresponding equivalent content.
Applications to the examination board must be submitted in writing. Please remember to provide your address, matriculation number and e-mail address if any queries become necessary. Please also state the semester in which you started your Master's degree program, so that we can assign your request directly to the valid examination regulations.
Studies and examinations that you have provided in University studies at a state or state-acknowledged university (home and abroad) or cooperative education may be credited upon request, provided the proven competencies match substantially with those of the MMDS degree program in Mannheim.
For the acknowledgement you have to hand in the following documents:
Please hand in the complete documents in notarized hardcopy to the examination board.
Note: A final decision on possible debits can be made only after enrolling at the University of Mannheim. Unfortunately, preliminary information cannot be provided.
The Mannheim Master in Data Science (MMDS) program equips students with the knowledge and skills necessary to gain operational insight from large and complex datasets. It is structured into the five blocks Fundamentals, Data Management, Data Analytics, Projects and Seminars, and the Master’s Thesis.
Fundamentals (0 – 14 ECTS)
The goal of the fundamentals block is to align the previous knowledge of students from different degree programs. Graduates from computer science and mathematics acquire the required knowledge in empirical research (in particular, data collection and multivariate statistics). Graduates from the social sciences and other fields acquire the required knowledge in computer science (in particular, programming and database technology).
Data Management (24 – 36 ECTS)
One of the central challenges in the Big Data area is to handle the enormous amount, speed, heterogeneity, and quality of the data collected in industry, the public sector, and science. The Data Management block covers methods and concepts for obtaining, storing, integrating, managing, querying, and processing large amounts of data. The block includes courses on modern data management technology (such as parallel database systems, Spark, and NoSQL databases), data integration, information retrieval and search, software engineering, and algorithms.
Data Analytics (30 – 54 ECTS)
The Data Analytics block forms the core of the study program. It provides courses ranging from data mining, machine learning, and decision support, over text analytics and natural language processing, to advanced social science methods such as cross-sectional and longitudinal data analysis. The range of methodological courses is enhanced by courses on optimization, visualization, mathematics and information, and algebraic statistics.
Projects and Seminars (12 – 16 ECTS)
The Projects and Seminars block introduces students to independent research and teaches the skills necessary to successfully participate in and contribute to larger data science projects. The block consists of research seminars, individual projects, team projects, as well as data science competitions. The projects are conducted jointly with industrial partners and/
Master’s Thesis (30 ECTS)
In the master thesis, students apply what they learned throughout the program. The master thesis has a duration of 6 months. Students are encouraged to write their thesis either in the context of research projects conducted by participating institutes or together with an industrial partner. Students often write their master thesis together with a company from the MMDS Industry Partner Network.
Note: This is just an example - your actual study plan may vary depending on the semester in which you start, your preferences, etc.
Members of the examination board for the course Mannheim Master in Data Science:
Prof. Dr. Paulheim
You can contact the examination board via pruefungsausschuss(at)wim.uni-mannheim.de
The official address is:
The student advisory (run by the study coach and the academic advisor) is a combined offer for the Master Degree of Mannheim Master in Data Science.
You can consult us in questions regarding:
You can contact the advisory service via studienberatung(at)wim.uni-mannheim.de.
In order to find a supervisor and a topic for the master thesis, early planning and initiative is necessary. First and foremost, as a student, you are responsible for finding direct contact with a chair that fits your study profile. This means that you proactively contact several chairs / professors to get a topic for your Master's thesis. It is most common that you find an agreement in this way and this way is desired by the faculty of you as a student.
Who can supervise my Master's thesis?
In general, all professors teaching in the MMDS also supervise master theses. However, professors from other faculties are also possible, given that the topic falls in the scope of the MMDS.
Industry Partner Network
MMDS students often write their master thesis together with a company from the MMDS Industry Partner Network. For more informaiton about open topics provided by partner companies please contact Prof. Dr. Heiko Paulheim.