Hasselt University

What you'll study

The programme builds a strong foundation in probability and statistical inference, then moves to applied and computational methods used for analysing complex and large-scale data. Core topics include probability theory, statistical inference, multivariate analysis, regression and generalized linear models, Bayesian methods, and time series and survival analysis. Applied and data-science oriented modules commonly cover machine learning, data mining, statistical learning, scalable algorithms for big data, reproducible statistical computing (R and Python), and database/query techniques.

Students typically follow a mix of compulsory and elective courses, allowing specialisation in areas such as Bayesian statistics, computational statistics, biostatistics, econometrics, or machine learning for high-dimensional data. The programme culminates in an independent research project or master's thesis; many students also take an internship or an industry project as part of the degree to gain practical experience.

Entry requirements

Applicants should hold a relevant bachelor’s degree in statistics, mathematics, computer science, engineering, economics or another quantitative discipline with sufficient background in calculus, linear algebra, probability and basic programming. Where background gaps exist, the admissions committee may require applicants to complete preparatory coursework.

Typical application documentation includes an official transcript, CV, a motivation letter describing academic and career goals, and at least one academic reference. The programme is taught in English; applicants whose prior degree was not taught in English are usually required to demonstrate proficiency in English through an accepted test or other documented evidence of prior English-medium study.

Career prospects

Graduates enter a wide range of roles where statistical reasoning and data skills are central. Common job titles include data scientist, statistician, data analyst, machine learning engineer, quantitative analyst, biostatistician and business intelligence specialist. Alumni find positions across sectors such as healthcare and pharmaceuticals, finance and insurance, tech companies and startups, public policy and government agencies, manufacturing and logistics, and academic or industrial research labs. The programme also provides a strong basis for doctoral study in statistics, data science or related fields.

Why study at Hasselt University

Hasselt University offers a compact, research-active environment with close supervision and accessible teaching staff. The university is known for applied quantitative research and collaboration with regional and national partners, giving students opportunities for internships and applied projects. Students benefit from modern computing facilities, hands-on coursework that emphasises reproducible analysis and scalable methods, and a curriculum that balances theoretical depth with practical data-science tools and workflows.