Education

As one of TUM’s Integrative Research Institutes, MDSI also has an educational mandate. It hosts the Interdisciplinary Study Program (ISP) Big Data, a recently established TUM format that pools and strategically plans the respective teaching activities across disciplines and departments. MDSI concentrates on developing innovative formats focusing on cross-departmental or cross-school activities covering both methodological foundations and state-of-the-art applications.

Linde and the MDSI support outstanding master's students with the Linde/MDSI Master's Scholarship.

Bioinformatics is offered jointly by TUM and Ludwig-Maximilians-Universität (LMU). It offers great freedom for individual specialization within the field.

Biomedical Computing (BMC) aims to further develop existing diagnostic and treatment options in medicine through innovative software solution and imaging techniques.

Biomedical Engineering and Medical Physics focuses on the application of new research-driven scientific principles in medicine and the life sciences.

Biomedical Neuroscience aims to teach both the theory and practice of neuroscience, as well as the fundamentals of neuropsychiatric disorders.

Computational Mechanics combines theoretical and applied mechanics as well as computer science, software engineering and applied mathematics.

Computational Science and Engineering (CSE) combines applied mathematics, computer science and scientific or engineering applications.

Data Engineering and Analytics deals with innovative solutions for handling and analyzing very large amounts of data.

Electrical Engineering and Information Technology deepens already existing factual and methodological knowledge and offers the opportunity for professional specialization.

ESPACE - Earth Oriented Space Science and Technology operates at the interface between spaceflight and the scientific and engineering use of satellite data.

Finance and Information Management (FIM) offers the opportunity to study the unique combination of finance and information management.

Computer Science broadens and deepens existing knowledge and offers the opportunity for individual specialization.

Mathematics in Data Science combines a high-profile education in mathematics with an emphasis on the burgeoning area of Big Data.

Mathematics in Operations Research deals with mathematical optimization and other subfields of applied mathematics.

Mathematics in Science and Engineering combines a broad education in mathematics with an applied subject such as physics, structural mechanics, fluid mechanics, or medical engineering.

Mechatronics and Robotics is aimed at those interested in the field of intelligent and digitally networked systems and advanced smart robot systems..

Robotics, Cognition, Intelligence connects various engineering disciplines such as mechanical and electrical engineering with computer science.

Software Engineering prepares graduates to assume responsible roles in research and industry as technology experts or decision makers.

Business informatics  is both theoretically sound and practical, and specifically prepares students for demanding careers with an IT focus.

Bioinformatics is offered jointly by TUM and Ludwig-Maximilians-Universität (LMU). It combines computer science with molecular biology, biochemistry and genetics.

Electronics and Data Engineering is aimed to equip students with the necessary skills and competencies in the emerging digital workforce.

Electrical Engineering and Information Technology provides a comprehensive scientific spectrum of methodological fundamentals for professional qualification or further master studies.

Computer Science provides solid theoretical, practical and technical skills.

Engineering Science imparts a broad basic knowledge in the field of engineering as well as in-depth knowledge of mathematics and natural sciences.

Business Information Systems combines computer science and business administration.

MDSI integrates the TUM Data Innovation Lab (TUM-DI-LAB), a novel teaching program for master’s students from any TUM department. In this program, the students team up to explore new data-driven approaches to interdisciplinary challenges.

Benefitting from a comprehensive mentoring and supervision system, students develop joint, practice-oriented, and data-driven research projects in close collaboration with innovative companies. The lab offers invaluable experience on how to conceptualize and conduct the most effective and practical education to train the next generation of digital experts and entrepreneurs in the field of data science.

MDSI cooperates with the TUM Institute for Life-long Learning (TUM-IL3) to design and subsequently provide learning opportunities on data-related topics in continued education.