Master of Statistics and Data Science
KU Leuven
Key Information
Campus location
Leuven, Belgium
Languages
English, Dutch
Study format
Blended, Distance Learning, On-Campus
Duration
2 years
Pace
Full time, Part time
Tuition fees
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Application deadline
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Earliest start date
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Introduction
The Master of Science in Statistics and Data Science is offered by the Leuven Statistics Research Centre (LStat), a privileged meeting space for statistics and data science researchers from a range of different domains and a stimulating environment for multidisciplinary statistical and data science research. You'll be trained intensively in both the theoretical and practical aspects of statistics and data science. The programme will help you develop a problem-solving attitude and teach you how to apply statistical methodology.
To tailor-make the programme to your needs and interests, you can choose one of the tracks:
- Statistics and Data Science for Biometrics
- Statistics and Data Science for Social, Behavioural and Educational Sciences
- Statistics and Data Science for Business
- Statistics and Data Science for Industry
- Theoretical Statistics and Data Science
- Interdisciplinary Statistics and Data Science
- European Master of Official Statistics (EMOS, on-campus only)
The programme can be followed either on campus in Leuven or in an online/blended format. When you choose the online/blended format, it is possible to compose your programme by only selecting courses that are offered fully online, and to graduate from the programme without ever coming to Leuven.
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Admissions
Curriculum
- On campus programme
- Blended/online programme
- QASS programme
Program Tuition Fee
Career Opportunities
The applications of statistics and data science are very diverse, just like your professional options. As a highly skilled statistician and data science expert, you'll be recruited by industry, banks or government institutions. Many graduates go on to designing clinical trials and supporting the biomedical sector, coaching research for new medicines, setting up and analysing psychological tests and surveys, performing financial risk analyses, statistically managing R&D projects and quality controls, or developing statistical software.