In 2004, when Frank Schweitzer started at ETH Zurich, he became part of the new Department of Management, Technology, and Economics (D-MTEC) and has been involved from the beginning in developing the curriculum for the new Master of Science program in Management, Technology, and Economics (MSc MTEC). This program is targeted at Swiss and international students with a technical background, who want to obtain additional qualifications in management and economics - to meet the requirements of leading technology oriented companies. At the same time, the scientific frontiers in management and economics have to be an integral part of this educational program, with ETH Zurich aiming to be a player in the top league of scientific research institutions.
For us, this meant developing completely new courses on subjects we had not dealt with before. The challenge is not only to pay attention to the requirements of practitioners, but also to provide a strong quantitative methodological background to advance scientific research on these topics. In all these courses emphasis is put on the quantitative understanding of socio-economic systems, to model their structure and dynamics and to optimize and design their behavior.
Currently, we offer three different courses at master level, which are all accompanied by extensive exercises. One of these courses, Systems Dynamics and Complexity, is a core courses of the MTEC curriculum. The ones on Complex Networks and Agent-Based Modelling of Social Systems are linked to the Department of Physics of ETH, with Frank Schweitzer being an associated member. Additionally, since 2008 we have been co-organizing the Interdisciplinary Seminar Modeling Complex Socio-Economic Systems and Crises for students and doctoral students, where internal and external speakers give talks every Tuesday during the semester.
Since 2017, we are also offering the course Social Data Science which focuses both on the fundamentals and applications of Data Science in the Social Sciences, including technologies for data retrieval, processing, and analysis with the aim to derive insights that are interpretable from a wider theoretical perspective.