Methods Center

M.Sc. Quantitative Data Science Methods

Psychometrics, Econometrics and Machine Learning

Thy symbolic picture represents the key areas of the program. It shows the face of a virtual person which has a globe where her brain should be in front of an illuminated skyline. Everything looks very "cyber".

New Module Handbook and Examination Regulation from 10/2023 on!

From October 2023 on we will have a new Module Handbook and a new Examination and Study Regulation (German version).

Some of the changes are:

  • more flexible structure to allow for changing lectures
  • more flexible obligatory courses depending our the previous experiences
  • possibility to name specialication in Master certificate

Mastering the Future of Information

Nowadays large amounts of data are ubiquitous. Areas of study within the social and behavioral sciences such as psychology and economics increasingly rely on the appropriate handling of these large amounts of data using quantitative methods. However, experts who are able not only to apply such methods but also to develop them and to reflect critically on their use are hard to find.

Become Part of an Interdisciplinary Avant-Garde

Cooperation

Tübingen has a strong research profile in all three core areas. Top-level researchers from all major methodological branches of Quantitative Data Science (QDS) will actively contribute to teaching on the program.This includes members of the Methods Center, the School of Business and Economics, the working group on Research Methods and Mathematical  Psychology (Department of Psychology) and Machine Learning experts of the Department of Computer Science.

Target Audience

This program is aimed at students with a mathematical, scientific or engineering background who are interested in Behavioral and Social Sciences as well as psychologists and economists who can provide evidence of having good mathematical and statistical knowledge (linear algebra, calculus). In addition, the Foundations module is intended to minimize possible differences in knowledge and skills resulting from the highly interdisciplinary nature of the student body. It will also be possible to select modules according to your individual needs and interests.