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Mannheim Master in Data Science

    General Questions

  • Why is it important to read the examination regulations?

    The examination regulations (Prüfungs­ordnung) state your rights and duties as a student of Mannheim Master in Data Science at your university.

  • Can I do a Module Change?

    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.

    Changing of a not yet passed module

    If you have chosen the wrong module, you have the opportunity to apply for a module change. The application must be submitted in written form using the form „module change request“ to the responsible examination board.

    To do this, use the following form:

    Please also note that any unsuccessful attemptswill be transferred from the original module to the new module!

    Please note furthermore that a module change does not influence the requirements of your examination regulations. In particular, the rules about the required credits in the different disciplines are still valid.

    You will remain registered for the original module until the end of the exam registration period. In case you are still registered for the original module after the exam registration period please contact Studien­büro I.

  • Why am I still registered for the original exam after a module change?

    In case you are still registered for the original module after the exam registration period please contact Studien­büro I.

  • How do I attend a team project?

    In the beginning of each semester, the business informatics institute organizes a session in which all chairs offering team projects introduce their topics. After that session, you enroll for a team project in Portal2, indicating your preferences.

  • Do I need to finish all of my exams before starting my Master's thesis?

    You have to finish at least 60 ECTS before starting your thesis, although some chairs might check whether you completed all your exams. Nevertheless, we clearly advise you to finish all exams first. Writing a master's thesis is a full time job, and it takes a lot of coordination and organization to take exams and write a thesis in parallel.

  • How do I conduct an individual project?

    Individual projects are offered by the chairs. In general, you should approach one of the lecturers offering courses in the MMDS and appoint the topic and scope of your project individually.

  • Can I study abroad for a semester?

    Yes, that is possible. To do so, you can refer to the list of partner universities of the business informatics and mathematics faculty (see list here) and the list of partner universities of the University of Mannheim.

    Since data science is a quite novel field, most of those are partners in the business informatics and business mathematics master's programmes, not in dedicated data science programs, and you have to check yourself whether the course catalogues contain a suitable amount of data science related courses. Depending on whether you select courses with a focus on computer science or mathematics, you have to apply either for a business informatics or business mathematics exchange.

    Details on how to transfer credits from studies abroad can be found here.

    More helpful information can be found on the web page of the International Office of the University of Mannheim.

    In case of questions, please contact Juliane Roth.


  • Studyplan and Timetable

    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/or support ongoing research efforts of participating institutes.

    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.

  • Examination Regulations and module catalogue

    The module catalogue 2019/2020 (Appendix) gives an overview of the courses and contents of the program.

    Please read the examination regulations of your program carefully.

  • Examination board

    Members of the examination board for the course Mannheim Master in Data Science:

    Chairman

    Prof. Dr. Paulheim

    Student representative

    Alexander Haberling

    You can contact the examination board via pruefungs­ausschuss(at)wim.uni-mannheim.de           

    The official address is:

    Prof. Dr. Heiko Paulheim

    Prof. Dr. Heiko Paulheim

    Prüfungs­ausschuss Mannheim Master in Data Science
    Universität Mannheim
    Fakultät für Wirtschafts­informatik und Wirtschafts­mathematik
    B 6, 26 – Raum B 0.22
    68159 Mannheim
    Sprechstunde:
    Di 9:00–10:00
    vorherige Termin­vereinbarung mit Bianca Lermer
  • Advisory Service

    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:

    • the study program
    • the module catalogue
    • the examination regulations
    • cases of hardship
    • questions about module changes
    • contents of courses
    • your study plan (modules, tracks, thesis)

    You can contact the advisory service via studien­beratung(at)wim.uni-mannheim.de.

    Samuel Broscheit

    Samuel Broscheit

    Fach­studien­beratung Wirtschafts­informatik und Lehr­amt Informatik
    Universität Mannheim
    Fakultät für Wirtschafts­informatik und Wirtschafts­mathematik
    B 6, 26
    Gebäudeteil B – Raum B 0.10
    68159 Mannheim
    Sprechstunde:
    nach Vereinbarung
    Birgit Czanderle, M.A.

    Birgit Czanderle, M.A.

    Studien­erfolgskoordinatorin, Studien­coaching Wirtschafts­informatik und MMDS, Kontaktstelle zum Prüfungs­ausschuss
    Universität Mannheim
    Fakultät für Wirtschafts­informatik und Wirtschafts­mathematik
    B 6, 26
    Gebäudeteil B – Raum B 0.05
    68159 Mannheim
    Sprechstunde:
    nach Vereinbarung, Anwesenheit Mo–Mi 10–13.30 Uhr
    Lisa Wessa, M.A.

    Lisa Wessa, M.A.

    in Elternzeit
    Universität Mannheim
    Fakultät für Wirtschafts­informatik und Wirtschafts­mathematik
    B 6, 26 – Raum B 1.04
    68159 Mannheim
  • Master’s Thesis

    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.