Research Master Business Data Science
Vrije Universiteit Amsterdam
Key Information
Campus location
Amsterdam, Netherlands
Languages
English
Study format
On-Campus
Duration
2 years
Pace
Full time
Tuition fees
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Application deadline
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Earliest start date
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Introduction
Research Master Business Data Science
The Research Master Business Data Science is a multidisciplinary research program with a central focus on the performance of academic research.
The English-taught Research Master Business Data Science prepares talented and motivated students to enter high quality PhD programs in Business at one of the three partner universities. It is a joint initiative of the Erasmus School of Economics of the Erasmus University Rotterdam (EUR), the Faculty of Economics and Business of the University of Amsterdam (UvA), and the School of Business and Economics of the Vrije Universiteit Amsterdam (VU).
This program is looking for students with strong analytical and quantitative skills.
Admissions
Scholarships and Funding
Several scholarship options are available. Please check the university website for more information.
Curriculum
The Research Master in Business Data Science is a two-year program consisting of 120 EC. It is tailored for recent Bachelor's degree graduates, or those currently still enrolled in an undergraduate degree program, 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 subdiscipline, selecting from among: 1) quantitative finance, 2) management science, and 3) supply chain 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.
Research Practice - Aligning skills and knowledge. The program 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 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.
Program Tuition Fee
Career Opportunities
The jumpstart for your PhD trajectory
The program helps students to jumpstart their PhD trajectory not only through solid training, but also with direct experience in research (provided during the seminars, research clinic, research hackathons, skill workshops, thesis, interaction with faculty, research assistantships opportunities), and teaching (e.g., teaching assistantships opportunities).