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Home | Graduate Program | Research Master

Research Master Business Data Science

Learn more about the two-year Research Master Business Data Science at Tinbergen Institute.


The two-year program (120 EC) in Business Data Science is designed to prepare future PhD students in the business and econometrics departments (spanning disciplines such as business analytics, human resources, finance, marketing, entrepreneurship, and more), with a strong focus on data science.  

This research master’s program is tailored for students with strong analytical and quantitative skills, providing rigorous training in preparation for a doctoral degree in business and econometrics departments. Students who successfully complete the research master’s program are supported in finding PhD positions at one of the three partner universities or elsewhere.   

Acquiring skills

In year 1, the primary objective is to build a solid data science foundation and expose students to a variety of methodological approaches. These skills are applied to various business disciplines in the field courses.

First year overview:

Block Business and Data Science (Advanced) Mathematics, Statistics and Econometrics Research
0 Introduction Refresher courses in Programming and Mathematics Business Foundations
I Decision Theory for Business Fundamental or Adv Mathematics; Statistics or Asymptotic Statistics Business Foundations
II Machine Learning I; Parallel Computing and Big Data Econometrics I or Advanced Econometrics I Business Foundations
III Machine Learning II Econometrics II or Advanced Econometrics II Business Foundations; Track-specific elective/Research; Hackathon/ Internship
IV Simulation Analysis & Optimization; Deep Learning Econometrics III or Advanced Econometrics III  
V Track-specific field course; Natural Language Processing   Skills Workshop; Research Internship/elective

 See full list of courses (EUR Course Catalog). 

Building knowledge

In year 2, students focus on a given business sub-discipline, selecting courses in a chosen sub-discipline: 1) quantitative finance, 2) management science, 3) operations analytics. The courses assigned for each of these sub-disciplines have been carefully selected by a team of experts with the aim of ensuring the perfect learning trajectory that will lead to substantive contributions in the fields of each particular sub-discipline. 

Second year overview: 

Block Business and Data Science (Advanced) Mathematics and Statistics Research
I Field-specific field courses, Research Internship, Electives    
II Field-specific field courses, Research Internship, Electives Bayesian Econometrics Skills Workshop II
III Field-specific field courses, Research Internship, Electives   Skills Workshop II; Thesis
IV     Skills Workshop III; Thesis
V     Thesis

Students also take the following courses in year 2:

  • Bayesian Econometrics
  • Research internships and/or electives
  • Skills workshops (review process, academic writing and presentations)
  • Research Master Thesis (30 credits)

See the full course list for year 2 and the Study Guide.

Academic and Examination Regulations

The Academic and Examination Regulations provide details on the program requirements and examination procedures and can be downloaded from the intranet.
 

> Program Outline