Interdisciplinary Electives
Interdisciplinary Electives enable students to gain insight into a specific application area of data science. These courses provide background knowledge and skills important for the respective area and enable graduates of the Data Science Mater’s program to bridge the gap between different academic disciplines.
Students must decide for one specific area within the Interdisciplinary Electives and attend at least two courses worth 8-12 credits within this area (see course compilations below). Students may choose courses within a course compilation at will, however, they are responsible for fulfilling respective course prerequisites. Importantly, the course selection must be approved by the mentor and made fix in the learning agreement.
Download Computational Biology, Bioinformatics, and Biomedicine (PDF, 96 KB)
Download Computer Networks (PDF, 93 KB)
Download Finance and Insurance (PDF, 100 KB)
Download Geographic Information Systems (PDF, 99 KB)
Download Law, Policy, and Innovation (PDF, 88 KB)
Download Neural Information Processing (PDF, 91 KB)
Download Robotics (PDF, 93 KB)
Download Social Networks (PDF, 93 KB)