The curriculum

An overview of your classes

First and second semester

During your first and second semester, you will take introductory classes in the areas Foundation of Data Analysis. Depending on the study focus  in your Bachelor's programme, you select classes totalling at least 24 ECTS. You have to select at least one course per focus area.

Focus Area Computer Science

Department of Computer and Information Sciences

  • Introduction to Computation for the Social Sciences (Winter Semester)
  • Datenbanksysteme (Summer Semester)
  • Algorithmen und Datenstrukturen (Winter Semester)
  • Konzepte der Informatik in combination with Programmierkurs I (Winter Semester)
  • Konzepte der Programmierung in combination with Programmierkurs II (Summer Semester) 

Focus Area Mathematics

Department of Mathematics and Statistics or Computer and Information Sciences

  • Mathematik für Wirtschaftswissenschaftler I (Winter Semester)
  • Mathematische Grundlagen der Informatik (Winter Semester)
  • Lineare Algebra I (Winter Semester)

Focus Area Statistics

Various departments

  • Statistik (Summer Semester, Politics and Public Administration)
  • Statistics I (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) 
  • Methoden der empirischen Politik- und Verwaltungsforschung (Winter Semester, Politics and Public Administration)
  • Empirie: Quantitative Methoden (Winter Semester, Sociology)
  • Methoden II (Summer Semester, Psychology)

Advanced Methods of Data Analysis 

Additionally, you take 36 ECTS  in the subject area Advanced Methods of Data Analysis.

These consist of 24 ECTS worth of classes and two seminars (6 ECTS each):

  • Probability Theory and Statistical Inference (Winter Semester, Department of Economics)
  • Research Design I (Winter Semester, Department of Politics and Public Administration)
  • Big Data and Scripting (Summer Semester, Department of Computer and Information Sciences)
  • 1 optional course
  • 2 seminars

Third and fourth semester

Your curriculum in the third and fourth semester depend on your chosen study track. You can choose between two tracks to customise your studies. 

Track A students

You take 20 ECTS worth of classes from the Master’s programmes of participating departments.

You select two modules totalling 20 ECTS from the Graduate School of Decision Sciences or the Doctoral Programme in Quantitative Economics and Finance and complete your Master’s thesis (3 months).

In addition, you accomplish a Data Analysis Project worth 5 ECTS.

Track B students

You take 25 ECTS worth of classes from the Master’s programmes of the participating departments.

You will complete your Master’s thesis with a processing time of 4 months.

In addition, you accomplish a Data Analysis Project worth 5 ECTS.

Example classes for the participating departments

Department of Computer and Information Sciences

  • Data Mining: Foundations
  • Data Warehousing and OLAP
  • Network Analysis

Department of Economics

  • Advanced Time Series Analysis
  • Financial Econometrics
  • Topics in Advanced Econometrics

Department of History and Sociology

  • Quantitative Data Analysis 
  • Survival Analysis
  • Categorical Data Analysis
  • Causal Analysis
  • Log-linear models

Department of Mathematics and Statistics

  • Zeitreihenanalyse
  • Multivariate Statistik
  • Mathematische Statistik

Department of Politics and Public Administration

  • Comparative Case Studies and Qualitative Comparative Analysis
  • Data Analysis with R
  • Data Analysis with Stata
  • Regression Models for Panel Data

Department of Psychology

  • Theory and Practice of Internet-based Research
  • Methods of Internet-based Research

You may choose any course from the module “Fortgeschrittene Forschungsmethoden und Diagnostik” and selected courses from the module “Kognitive und Affektive Neurowissenschaften”.