Master in Quantitative Data Science Methods – Psychometrics, Econometrics and Machine Learning (QDS)

The Quantitative Data Science Methods (QDS) Master's programme at the University of Tübingen is a four-semester, research-oriented degree that develops methodological expertise across three core areas: Psychometrics and Mathematical Psychology, Econometrics, and Machine Learning. The programme is designed to train graduates who can not only apply quantitative methods but also evaluate and develop them. It prepares students for doctoral study and for leading roles that require independent scientific judgment. The curriculum is organised into four areas. A Foundations area covers general statistical and technical modules and can be used to address gaps from prior study; this area is best completed in the first two semesters. The three core areas then deepen specialised knowledge: Psychometrics introduces latent variable modelling, item modelling, Bayesian statistics, and knowledge space theory among other methods; Econometrics covers time series analysis, machine learning applied to microeconometrics and financial markets; and Machine Learning addresses data literacy, deep learning, and statistical and probabilistic machine learning. A Data Ethics component runs alongside these areas, and a Project Seminar requires each student to carry out an independent research project in one of the core disciplines. The degree programme is located at the University of Tübingen in Tübingen, Germany, and carries an annual tuition fee of 3,000 EUR.