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Mannheim Master in Data Science

    Learning Agreements

  • Which Learning Agreement is there?

    Learning Agreements are a reassurance that the courses you choose will be recognized after you have passed them and return from abroad.

    There are two procedures of recognizing grades from abroad:

    •  Direct recognition as an equivalent course
    •  Indirect recognition as „Additional Course“

     

    Direct Learning Agreement

    In the case of direct recognition, it is necessary to have an equivalent course based on the „acquired competences“. So, if you identify a course at a university abroad that is largely the same (> 66% agreement) based on the course description, you can issue a direct learning agreement for this course. This course will then be filled with the grade from abroad. Contact persons for direct learning agreements are always the chairs that offer the course here in Mannheim.

    Indirect Learning Agreement

    If there is no direct equivalent to a foreign course in the local module catalog, but the module fits thematically into the field of „Data Management“, „Data Analyses“ or „Projects and Seminars“, then an indirect recognition can take place as "Additional Course Data Management“, „Additional Course Data Analyses“ or „Additional Course Projects and Seminars“. In total, the recognized courses may not exceed 18 ECTS.

    The contact person is the chair whose area of interest is closest to the course that is being requested, or if you are not sure the program management of the MMDS.

    ECTS for Indirect Learning Agreement

    The ECTS for the MMDS Additional will be determined by the examination board, were we convert the credits of the host university. As a result of this conversion you might get more than 6 ECTS or less than 6 ECTS for a course! Keep in mind that in the Master programs at most 18 ECTS in total can be recognized as additional courses! For universities in European countries, the credits are usually already ECTS or credit systems that are equivalent to ECTS.  

    Which form of learning agreement is better: indirect oder direct?

    Since the number of direct recognitions is not limited like the Additional Course is, this form should always be the preferred choice! With a direct recognition you also don't have the issue with ECTS conversions that do not fit in the scheme of your program.

  • Process for a Learning Agreement – What do I have to do?

    Once you have been approved for a partner university (in the case of Free Movers the approval comes directly from the foreign university), you should start to take care of your Learning Agreement. You should make the Learning Agreement before you go abroad. Thus you are on the safe side and know what courses abroad are then approved here for your studies.

    The learning agreement consists of two forms:

    The process of getting the courses from abroad recognized is split in two phases: 

    1. Before you leave abroad but after the commitment for a partner university visit the different chairs to get the OK for the approval of the particular course using the Learning Agreement Form. The  contact persons for courses of the Philosophical faculty, business mathematics, business administration, and economics are: 
    2. After your return from abroad please hand in the following four documents to your repsonsible Examination Board at the School of Business Mathematics and Informatics:  
      • Form „Anrechnung ausländischer Leistungen"
      • Transcript from the partner university
      • Learning Agreement(s) signed from the regarding Mannheim chairs and the cover form  
      • Confirmation of the International Office on submission of the field report


    Your documents will be checked and then the scores are converted. Foreign notes will be recognized at the University of Mannheim on the basis of these conversion tables. Following the examination then you will get back your originals, the student service office receives a copy.

  • Which forms do I need for Learning Agreement?


  • 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.