Curriculum

During the first semester every MSc SEDS student takes the introductory module Introduction to Computational Methods for the Social Sciences (9 ECTS).

During your first and second semester you will also take introductory (bachelor) classes in the module Foundation of Data Science. Depending on the study focus in your Bachelor's programme, you select classes totalling at least 18 ECTS. After the second semester every MSc SEDS student will have covered the following focus areas with at least one course (including the recognized courses from the admission requirements).

Focus Area Computer Science

Department of Computer and Information Sciences

• Data Visualization (summer semester)
• Konzepte der Informatik in combination with Programmierkurs I (winter and summer semester)

Focus Area Mathematics

Department of Mathematics and Statistics or Computer and Information Sciences

• Diskrete Mathematik und Logik (winter semester)
• Analysis und Lineare Algebra (summer semester)
• Datenmathematik (winter semester)
• Mathematik für Wirtschaftswissenschaftler I (winter semester)
• Lineare Algebra I (winter semester)

Focus Area Statistics

Various departments

• Statistik (summer semester, Politics and Public Administration)
• Statistics 1 (winter semester, Psychology)
• Statistics I (summer semester, Economics)
• Statistik I (summer semester, Sociology)

Focus Area Social-scientific Methods

Various departments

• Econometrics I (summer semester, Economics)
• Introduction to Survey Methodology (winter semester, Politics and Public Administration)
• Research Design I: Research Design and Causal Inference (winter semester, Politics and Public Administration)
• Methoden der empirischen Politik- und Verwaltungsforschung (winter semester, Politics and Public Administration)
• Empirie: Quantitative Methoden (winter semester, Sociology)
• Methoden und Geschichte der Psychologie (summer semester, Psychology)
• Research Methods 2 (winter semester, Psychology)

You continue your programme with advanced courses from 4 modules:

1.     Module Advanced Methods: Computer Science (18 ECTS)
Example classes: Big Data Management and Analysis, Algorithmen und Datenstrukturen & Programmierkurs II, Datenbanksysteme

2.     Module Advanced Methods: Statistics (18 ECTS)
Example classes: Probability Theory and Statistical Inference, Advanced Econometrics, Microeconometrics, Research Design II: Statistical Modelling and Inference

3.     Module Programming and Scripting (12 ECTS)
Example classes: Data Analysis with R, Programmierkurs I, II and III

4.     Module Social Science Applications (18 ECTS)
Example classes/projects: Computational Social Science Seminar, Advanced Data Challenge Seminar, research project from the participating departments (DSP), internship

You will complete a colloquium (3 ECTS) and your master’s thesis (24 ECTS, processing time: 4 months).