Mannheim Master in Data Science

Machine learning, artificial intelligence,and big data play a central role in modern information systems. The Mannheim Master in Data Science equips students with advanced expertise in machine learning, artificial intelligence, and large-scale data management. The program blends an extensive course selection with practical projects and research opportunities. Students acquire skills in collecting, organizing, and mining large amounts of data, and learn to apply these skills for data-driven problem-solving in various fields.

The curriculum comprises fundamentals in machine learning, data mining, data security, and data management, as well as a wide range of elective courses in areas such as deep learning, text analytics, computer vision, process mining, data integration, reinforcement learning, and optimization, among many others.

The Mannheim Master in Data Science offers a wide variety of courses that students can choose from, and a large degree of freedom to compile a curriculum based on individual interests. The course offerings include technical courses in the area of data analytics and data management, as well as courses on applying machine learning techniques to different types of data and within different application domains.

Thanks to close interdisciplinary collaborations between the School of Business Informatics and Mathematics and the School of Social Science, the School of Business, and the School of Humanities, MMDS students can also choose from various methodological as well as applied courses offered by these schools.

Mannheim is located in the Rhine Neckar metropolitan region, where large companies such as SAP, ABB, BASF, Roche, and Heidelberg Materials have their headquarters. Moreover, hundreds of innovative startups are located in the area. Every semester, hands-on projects with partner companies are offered in the study program, allowing students to get in touch with businesses and enhance their networks. Many students eventually choose to write their master’s thesis in one of those companies.

With 40 places per year, the class size of this program of study is rather small. Students in the master’s program Mannheim Master in Data Science thus benefit from a low student-to-teacher ratio and individual and personal contacts to the teaching staff.

The University of Mannheim is part of a global network. The university’s ties to more than 450 partner universities all over the world do not only impact life on campus, but also open numerous doors to those students who wish to study abroad for a semester. In addition, the Engage.EU network allows students to attend online courses at partner universities all across Europe.

The amount of data collected, as well as the progress of data mining and artificial intelligence methods have led to a growing interest in data-driven problem solving in companies, civil service institutions, and in research. As this development is ongoing and is even accelerated by the current boom in artificial intelligence, the job opportunities for data scientists are excellent and are also expected to stay excellent for the time to come. Graduates of the Mannheim Master in Data Science can thus choose from a wide range of opportunities in industry, civil service, and academia.

No matter whether you aim at working as a data scientist or AI specialist in a company, a civil service organization, or plan to follow the path to a PhD as an academic researcher, the Mannheim Master in Data Science provides you with an excellent study program to support your future career.

Students in the master’s program Mannheim Master in Data Science should

• be interested in IT and programming,
• have a general understanding of statistics and mathematics,
• be innovative,
• be capable of analytical thinking.

Note: this page describes the updated structure of the MMDS for students starting from HWS 2024. Students who started earlier find information on their study program here .

The master’s program comprises seven blocks:

• Data Science Fundamentals (27 ECTS)
• Data Management (6–24 ECTS)
• Data Analytics Methods (12–36 ECTS)
• Responsible Data Science (3–7 ECTS)
• Data Science Applications (0–12 ECTS)
• Projects and Seminars (14–18 ECTS)
• Master’s Thesis (30 ECTS)

The data science fundamentals block comprises four mandatory courses in data mining, machine learning, large-scale data management, and data security and privacy. The data management block teaches data management methods from database query optimization to blockchains. The data analytics methods teaches data mining methods for different kinds of data, such as text, image, process, and social network data. In the responsible data science block, students learn to judge the societal impact of data science and AI. The data science applications block comprises courses offered by different schools, such as business, humanities, and social science, which discuss data-driven methods in different application areas. Finally, in projects and seminars, and in the master’s thesis, students conduct their own research projects, both individually and in teams.

In our selection process, we take numerous criteria into account. For more details, please check the selection statutes (see below).

Essay
In addition to your application documents, you must submit an essay in English or German of at least 5,000 words written during the course of studies (e.g. a bachelor’s thesis) with a subject-specific focus on Data Science, Mathematics, Informatics or Statistics. The text must comply with the general rules for academic writing and research.