Programme overview

Research Master Business Data Science
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The Research Master in Business Data Science is a two-year programme consisting of 120 ECTS. It is tailored for recent Bachelor's degree graduates, or those currently still enrolled in an undergraduate degree programme, who are looking to pursue a solid course of training leading to a doctoral degree.

Data Science Foundation

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.

Business Foundation

Building knowledge

In year 2, students focus on a given business sub-discipline, selecting from among: 

  1. management science (entrepreneurship and innovation, marketing science, human resources and organisation, knowledge and information networks, management and strategy)
  2. operation analytics 
  3. quantitative finance and accounting

The courses have been carefully selected by a team of experts with the aim of ensuring the perfect learning trajectory in each subfield.

Research Practice

Aligning skills and knowledge

The programme starts with an overview of the business problems that data science can address (in block 0), which also exposes students to fundamental components of the different business fields. This early exposure helps students to absorb and process materials presented later in courses on methodology, with respect to the various business perspectives. Students become further acquainted with the different business fields during seminars held throughout the first year, for which they will have to write a research proposal, as well as during the research hackathon.

The research internship and research hackathon makes students think about how to approach the problems that arise in the various disciplines, and puts their knowledge to the test. Finally, the research clinic and the Research Master thesis represent students' final moments of integrating business and data science, and will showcase their ability to identify relevant problems and address them using cutting-edge techniques to make a substantive contribution to the field.

Next to taking courses, students are encouraged to select a research topic for the final thesis and to actively explore potential supervisors. The final thesis is a research project, set up by the student under experts’ supervision. The matching of students and supervisors, while largely the results of individual communication between the two parties, is supported by the DGS.

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