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Что я буду изучать?

Statistical techniques used in the Social and Behavioral Sciences, Economics and Data Science are strongly connected and share an interdisciplinary basis. The collaboration between these disciplines is therefore very important in the context of methods development and application. We train people who can develop and apply methods at this interdisciplinary intersection.

The international MSc Program “Quantitative Data Science Methods: Psychometrics, Econometrics, and Machine Learning” (QDS) is a unique research-oriented two-year study program designed for students interested in cutting-edge quantitative methods used in these three disciplines and in the flexible transfer of methodologies between them.

The core modules introduce quantitative methods in the fields of psychometrics, econometrics and machine learning, as well as providing students with interdisciplinary knowledge in statistics, study design and programming.

Elective modules (such as research-oriented project modules and an ethics module) allow for an individual research focus in an elected area.

Special features of the program are:
• Individual research projects with possible integration in ongoing research at an early stage (3rd semester).
• Opportunity to start the Master Thesis early (3rd semester).
• Studies abroad (3rd semester).
• All modules are taught in English.

What is special about the Tübingen program?


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 from the Department of Computer Science.

Why QDS @ Tübingen ?

• offers a modern, interdisciplinary curriculum in quantitative methods
• sits at the intersection of Psychometrics, Econometrics and Machine Learning.
• is organized by the Methods Center which is a new core facility for methods development funded by the German Universities Excellence Initiative
• has highly motivated teaching staff
• offers research and studies on an international level with many contacts to universities abroad (with opportunities for student exchange)
• and last but not least: Tübingen is a pretty historic town with a lively student culture

Career prospects

QDS graduates will be able to start a career in every area of statistical application or research. The interdisciplinary character of the program opens a broad field of opportunities. Key positions for QDS graduates include:

•Statistical consultancies
•Data Analyst / Scientist (financial sector, industry, ...)
•Insurance companies
•Industrial and academic research

The QDS program is also an excellent foundation for doctoral studies, both at university and in industry.

На каком факультете я буду учиться?

Faculty of Economics and Social Sciences

Варианты обучения

Очная (4 семестр)

1,500 euros per semester since the winter semester 2017/18; In addition, there are the usual semester fees of 158.30 euros
Начало обучения

Предполагаемое начало: Октябрь 2022


University of Tubingen



Baden Wurttemberg,

72074, Germany

Вступительные требования

Для студентов, проживающих в Соединенных Штатах

Students must have a Bachelor’s degree. In addition, they must be fluent in German and solid in English.

Для иностранных студентов

Bachelor’s degree or equivalent in a field that includes a mathematical or statistical focus (mathematics, data/computer science, physics, economics, quantitative psychology and related fields) with an overall grade better than 2.5 (This refers to the German system where 1.0 is the highest. For queries concerning the equivalence of non-German qualifications please contact the program advisor.)
• Applications must include evidence of proficiency in the following fields: one-and multi-dimensional calculus, linear algebra, and either statistics or probability theory.
• Strong background in mathematics, statistics and probability theory

• Basic/First knowledge in programming, algorithms, and data structure is required.
• English language requirements


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