Master of Statistics and Data Science
Why study Master of Statistics and Data Science at UHasselt?
Two year (120 ECTS) • English programme
- Become an expert in data analysis with a direct relevance to societal issues
- Flexible and student-centered education: study on campus, online or combine your studies with work
- Learn from internationally renowned experts in statistics and data science
- Specializations in: Biostatistics, Bioinformatics, Quantitative Epidemiology and Data Science
- Strong demand on job market
- Accredited by the UK Royal Statistical Society (RSS)
- Get to know Hasselt University
About the programme
The English two-year programme "Master of Statistics and Data Science" at Hasselt University combines a solid study of principles of statistics and modern data science, with a focus on applications in the life sciences (e.g. clinical trials, epidemiology, public health, genomics, …).
Our approach to teaching
The Master of Statistics and Data Science is quite unique in the sense that (1) it offers a statistics education with a good sense of general data science, and (2) it offers a data science specialization with a very sound understanding of important statistical concepts and solutions.
In order to meet the needs of a broad population of interested students, five different programme profiles are available: on-campus, distance learning, shortened programme, VLIR UOS ICP and working student, but not all profiles can be combined with all four specializations.
The Master of Statistics and Data Science is an RSS accredited programme. In the 33 years of its existence, over a thousand students from all over the world have graduated and started a career in industry, government, research, ...
Safety during COVID-19 pandemic
We have developed a resilient and flexible blended learning format that easily allows moving forward and backward between on-campus and on-line formats. Our lecturers have profound experience in on-line teaching, given that we have been running a distance-learning programme for about 10 years. Depending on the epidemiological situation, in Belgium or in your home country, and at any time in the year, each individual student can participate in the preferred formats and can move from one to another, depending on his/her personal situation. You will be supported towards group work and interactions among you, also when these take place electronically.
Our on-campus programme takes a blended form, with on-campus lectures, project work and contact moments when possible, but also with on-line teaching materials and Q&A sessions when on-campus activities cannot proceed or cannot be attended.
Specialisations
Choose one of 4 specializations to focus your studies
Four specializations are offered: Biostatistics, Bioinformatics, Quantitative Epidemiology and Data Science. All specializations provide a solid basis of data science, but the first three put more emphasis on statistics. The Data Science specialization still has a good statistics basis, but offers more courses on other aspects of data science (e.g. data visualization, data management, programming and algorithms, …).
Biostatistics
Biostatistics
The specialization 'Biostatistics' focuses on statistical methods that are important for many different applications in the life sciences, including clinical trials.
Statistics in general, and biostatistics in particular, rests on solid mathematical and probabilistic foundations. This is why in both the first and second year, foundational courses are offered, in a step-up design, with the lighter versions offered during the first year. At the same time, the field’s strong focus on the bio-sciences is supported by a broad introduction to medical and molecular biology.
The practicing biostatistician needs to be equipped with important modeling tools, such as linear models (regression, analysis of variance, etc.), generalized linear models (logistic regression, Poisson regression, etc.), multivariate methods, longitudinal data analysis methods, Bayesian methodology, time-to-event analysis, and so on. Evidently, fluency in the use of statistical software is expected, which is why not only dedicated courses but also assignments and course work throughout many courses focus on the computational aspects. Further, specialized courses are offered in clinical trials, omics data, spatial statistics, infectious diseases epidemiology, microbial risk assessment, and so on.
Biostatisticians must be able to communicate with researchers from various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
For more detailed information on the curriculum of this specialization, please consult the study guide.
Bioinformatics
Bioinformatics
Technological developments in molecular biology over the last few decades have improved the knowledge of molecular and cellular processes underlying e.g diseases and responses to treatments. “Omics”-oriented approaches (such as genomics, transcriptomics, microbiome or proteomics) consider many molecules of a given type collectively instead of one molecule at a time, generating a system-wide understanding. These technologies can nowadays even be applied at a single cell level. Data obtained with the help of “omics” technologies are usually very voluminous (yielding even millions of measurements per single biological sample or per cell in a sample), highly structured, and complex.
Analysis of such data is not trivial and has become a specialty of its own. Of course, good knowledge of statistical methodology is required and training in this respect is offered in the first year of our program. Additionally, an introduction to medical and molecular biology is offered, together with a decent training in programming. The second year focuses on the methods specific for the analysis of genomic,proteomic and microbiome data obtained by using technologies like next-generation sequencing, mass spectrometry, etc. Methods for integrative analyses of different types of data are considered, too.
Bioinformatics is an interdisciplinary science. Statisticians working in this domain need to be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
For more detailed information on the curriculum of this specialization, please consult the study guide.
Quantitative Epidemiology
Quantitative Epidemiology
The specialization 'Quantitative Epidemiology' focuses on the design and analysis of epidemiological studies, including the mathematical modelling of infectious diseases.
The design of epidemiological studies and intervention measures, and the collection and analysis of epidemiological data require appropriate expertise in statistical methodology in combination with knowledge of other scientific disciplines such as medical biology, computer sciences, data management, social sciences, etc.
Statistical methodology for epidemiology rests on solid mathematical and probabilistic foundations. This is why foundational courses are offered, in a step-up design, during the first year, supported by a broad introduction to medical and molecular biology, linear models (regression, analysis of variance, etc.), generalized linear models (logistic regression, Poisson regression, etc.), multivariate methods, longitudinal data, Bayesian methodology, so on. An introduction to epidemiology is also provided in the first year. During the second year, in addition to three foundational courses, specialized courses are offered in spatial epidemiology, digital epidemiology, mathematical modelling of infectious diseases, environmental epidemiology and microbial risk assessment.
Evidently, fluency in the use of statistical software is expected, which is why not only dedicated courses but also assignments and course work throughout the courses focus on the computational aspects.
Statisticians must be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
For more detailed information on the curriculum of this specialization, please consult the study guide.
Data science
Data science
The specialization 'Data Science' is built on the handling, managing, visualizing and analysing many different types of complex and/or big data sources, with a focus on modern programming and computing environments, and with a solid knowledge of statistical principles.
With the advent of the big data era, several global challenges that were outside of reach can now start to be addressed. In the field of medicine, wearable devices and real-time sensors generate huge amounts of data that can shed light on triggers for disease episodes. Omics and genome sequencing can aid in managing and preventing diseases, especially if they are combined with other data sources such as information from social networks. Integrated analysis of weather data, credit card transactions and air pollution data sheds light on how people change their behaviour due to air pollution. Graph analysis of social network data makes it possible to identify fake accounts and fake news - a growing problem in the current political climate. The list goes on... A data scientist is someone who, apart from technical skills to tackle these issues, has a desire to dig deeper and go beneath the surface of a problem.
The Data Science specialization of the Master of Statistics and Data Science provides a comprehensive education in this field, covering the whole data science cycle from data gathering, cleaning and management, to analysis and visualisation, and finally dissemination. Apart from a very decent knowledge of statistical principles, the topics in the master therefore include (but are not limited to) data and software carpentry, programming in Python and R, statistics, algorithms, machine learning (including deep learning), and data visualisation. In addition to regular courses, students can integrate their knowledge and skills in several data science projects and a hack week.
Statisticians/data scientists must be able to communicate with researchers of various fields, report results, and give effective presentations. Developing such skills is an integral part of the program.
For more detailed information on the curriculum of this specialization, please consult the study guide.
For ICP scholarship students the optional courses are fixed.
First year:
- First semester : Project: Learning from Data – 5 ECTS
- Second semester : Design of Agricultural Experiments – 4 ECTS
Second year
- First semester : Capita Selecta of Computational Biology – 3 ECTS
See the study guide for a detailed overview of the courses in each specialization.
Course outline
First year
First semester
The introductory phase, situated in the first semester of the first year, provides thorough fundamental knowledge of statistics, data management and programming (R, Python and SAS). Students will become familiar with data structures, statistical analysis, and, first and foremost, statistical concepts and reasoning. Apart from topic-related subjects, such as regression analysis, quite some attention goes to soft skills such as working in groups and reporting.
Second semester
In the second semester of the first year, the focus shifts from univariate models for continuous data to discrete data models and nonparametric approaches, as well as to correlated outcomes, combined with the discovery of associations. Within the second semester 3 subjects are common to all specializations, 2 courses are specific for your specialisation and there is room for 1 optional course.
Second year
The second year offers more specialized subjects. Each specialization offers a minimum of 27 ECTS of compulsory, specialized subjects. The master thesis of 24 ECTS is the main study/work subject of the second semester, and can be linked to an internship. Students are also invited to broaden their horizons by taking an optional course from the other specializations.
Reduced trajectory
Students that have already acquired a quantitative master (e.g. mathematics, (bio) engineering, ...) or a PhD degree that included a solid initial training in statistics, can receive a substantial number of course exemptions when applying for the programme. The Admission Board decides on these course exemptions after a thorough evaluation of knowledge and skills, resulting in a tailor made programme for the student. This is available in the on-campus and the distance learning track, and both part-time as well as full-time.
How do ECTS credits work?
The university decree for Flanders is built around a credit point system that is based on the principles of ECTS (European Credit Transfer System). Each year of a full-time degree programme counts 60 credits. Ideally, these credits are equally spread over two semesters, i.e. 30 credits per semester. Given that the expected total study load per year ranges from 1,500 to 1,800 hours for a full-time programme, one credit represents a study load of 25 to 30 hours. Study load includes time spent in class, personal work and exams.
Course overview
You can find all information regarding the study programma in the study guide.
Career prospects
In the past 30 years our graduates of the Master of Statistics and Data Science have found interesting jobs in the area of statistics in a wide range of sectors and in locations all over the globe.
Examples include sectors and jobs like:
- Applied and fundamental research at universities and research centers in scientific, pharmaceutical, biotechnical and medical disciplines (PhD, research associate, scientist, ...);
- Governmental authorities and non governmental organizations focusing on public, international and global health, environment, genetics, agriculture, sustainable development, ...;
- Independent statistics consultant;
- Education (lecturer, teaching assistant…);
- Tech Manager programming;
- Biometrics specialist;
- Senior Statistical Programmer;
- Data Analyst/Scientist.
As a service to our future graduates and alumni, we maintain a list of current job openings, brought to our attention by alumni, companies, research institutes, ...
Every year, master students from around the world study at Universiteit Hasselt and find it a life-changing experience. Find out what our students & alumni say about their experience and where it has taken them.
Interested in what our alumni have to say? Visit their dedicated LinkedIn group and Facebook page.
Ways to study
Study on campus
The Master of Statistics and Data Science is fully offered as a two-year on-campus programme. Enrolling for the on-campus programme means you will take classes on the campus, augmented with hybrid teaching, such as scheduled online learning activities.
The on-campus programme can be followed in full time, but also in part time, allowing for a flexible and feasible combination of work and study.
Assessment and Examination
Students of the on-campus programme take their assessments and examinations on campus. Examinations are organized in January and in June, each period lasting three to four weeks. The retake exams take place from mid August til the beginning of September.
International Course programme (ICP) – for students from developing countries
"The need for well-trained (bio-)statisticians and bioinformatics continues to rise worldwide"
The Flemish Interuniversity Council (VLIR-UOS) offers 10 scholarships each year for our ICP Master’s programme Master of Statistics and Data Science which is adapted to the specific needs and interests of statistics in developing countries.
The ICP Master of Statistics and Data Science offers a 2-year international and multidisciplinary training in statistics. The Master combines a solid study of fundamental methodology such as linear and generalized linear models, Bayesian modeling and multivariate models, with up-to-date training in topics such as clinical trials, public health, longitudinal data, survival analysis, genetics, survey methodology… In addition, there is a high focus on applications in state-of-the-art statistical software packages.
The programme is adapted to the specific needs and interests of statistics in developing countries.
You can choose between 3 specializations:
- Biostatistics
- Bioinformatics
- Quantitative Epidemiology
The specialization Data Science is not included in the ICP scholarship.
> Find out more information about ICP
> Find out if you are eligible for an ICP scholarship
Distance learning: Study from home
The Master of Statistics and Data Science is also fully offered as a distance learning (DL) programme. Enrolling for the DL programme means that as a student you will take the programme from a distance, i.e. from home, workplace or virtually any place with access to the internet. The DL programme can be followed full-time, or part-time, allowing for a flexible and feasible combination of work and study.
All study materials are provided to you online (e.g. web lectures and reading materials), together with clear guidance from the lecturers and with online Q&A sessions with the teaching staff. This allows you to organise your study work as you please. However, all homework and project assignments, and the report submission deadlines, are identical to those for the on-campus students. Just as for the on-campus students, you will receive feedback on your assignments.
Assessment and Examination
The exams are also the same as for the on-campus students, except that we organise these exams online for the distance learning students. The policy of online exams will be continued in 2022-23 and probably also in the years thereafter.
Exams are always organised during the office hours in Belgium (i.e. between 8h00 and 18h00 CET), regardless whether they are online of on-campus.
Working students
If you are working, part-time or full-time, it is possible to ask for additional support and educational and/or exam facilities which can make it more feasible to combine your job with studying. Students, both on campus and distance learning, who are working are advised to register for a part-time programme to maintain a proper balance between personal life, working and studying.
A good way to estimate how much time you’re going to spend on your studies is by using the ECTS (European Credit Transfer System). ECTS credits give an indication of the study load and 1 ECTS represents a study load of 25 to 30 hours (incl. lectures, self-study, projects, exams, …)
An example of a part-time programme of around 30 ECTS credits to start your first year of the master (study load of 750 to 900 hours):
- Concepts of Probability and Statistics (5 ECTS, semester 1);
- Linear Models (5 ECTS, semester 1);
- Data Management/Programming in R/Programming in Python (2 out of 3 courses, depending on the specialization, 8 ECTS in total, semester 1);
- Generalized Linear Models (6 ECTS, semester 2);
- Project: Multivariate and Hierarchical Data (8 ECTS, semester 2).
It is possible to individualize your part-time programme taking into account your academic background, but modifications should respect the chronology of courses. Also take into account the prerequisites of the 2nd year courses.
More information can be found on Studying-and-working at UHasselt.
Admission requirements
The Master of Statistics and Data Science has specific admission requirements, related to English language and diploma.
Diploma requirements
Candidates should hold at least an academic bachelor degree or a diploma of higher education equivalent to an academic bachelor degree (180 ECTS credit points).
Holders of a Belgian academic degree
Admission is given directly to holders of an academic bachelor or master degree in mathematics, statistics or bio/civil engineering.
Holders of Belgian academic degrees in the disciplines physics, computer sciences, chemistry, biology, life sciences, business engineering, medicine, sociology, psychology, artificial intelligence and biotechnology can apply for the programme. Their applications will be evaluated individually by the Examination Board.
Holders of an international academic degree
Admission of international degree holders will be evaluated individually by the Examination Board.
Holders of an international academic bachelor or master degree in mathematics, statistics, physics, computer sciences, chemistry, biology, life sciences, bio-, business-, civil engineering, medicine, sociology, psychology, artificial intelligence, biotechnology can apply for the programme.
Holders of an international academic bachelor or master degree in another discipline can also apply, provided they have successfully obtained an academic degree with at least one but preferably two courses in introductory statistics, and a sufficient background in mathematical and/or quantitative subjects.
It is requested to provide for an English version (or translation) of the course description of the already followed statistical, mathematical and other quantitative courses, with for each course a brief description of the objectives, the main topics, the workload and the course materials used. You can also copy that description from the program website of your university.
Holders of an international academic degree are strongly recommended to include the GRE general test result in their application; there are no minimum score requirements for the GRE general test. The institutional code of Hasselt University for the GRE test is 3112.
Language requirements
Candidates who wish to register in an English master’s programme need to have good English language skills, both written and spoken.
Candidates have to demonstrate their English language skills by a recent score on the Test of English as Foreign Language (TOEFL, with an internet-based score of at least 89) or the International English Language Testing System (IELTS, with an overall band score of at least 6.5). Do note that we only accept academic TOEFL or IELTS test results.
The English language test can be waived if your English language proficiency is proven otherwise (if higher education was in English or if English is a national language in your home country).
Candidates with a Belgian academic degree do not have to take an English language test.
Foreknowledge
We highly recommend you to have a look at the summary of topics in mathematics and statistics (pdf, 205 KB) which are considered as prerequisite knowledge in all or many courses.
Math for Stats E-summer School
In order to be better prepared for your Master of Statistics and Data Science studies at Hasselt University, we have developed an e-learning module of Mathematics useful for Statisticians (Math for Stats E-summer School ). The e-module takes place over a period of 3 weeks each year in the period August/September. At the end of each week a quiz is made available allowing you to test your mathematical skills. The self-study material contains the key mathematical concepts, examples, exercises and R-software code. During the e-learning module you have the opportunity to ask questions about the mathematical concepts (using a discussion forum).
The purpose of this e-learning module is to refresh and/or enlarge your mathematical and statistical knowledge. The module is fully available online and consists of several self-study documents. In this manner you can study at your own pace. The mathematical topics covered in this e-learning module are very important during your masters study in statistics & data science at our university.
All students that will enroll in the Master of Statistics and Data Science will receive an invitation email to participate in the E-summer School. Students need to be registered on time to be able to participate.
Admission and enrolment
For more information about the admission and enrolment procedure, please follow the link below
Take me to the admission procedureScholarships
International students can apply for a scholarship to the Master of Statistics and Data Science.
Master Mind scholarships
Master Mind scholarships for master students (for outstanding students only)
The programme aims to promote the internationalization of the Flemish Higher Education.
Check if you are eligible for a Master Minds scholarship
International Course programme (ICP) – for students from developing countries
Each year, 10 exceptional students from developing countries receive a full ICP scholarship for the Master of Statistics and Data Science. The programme is adapted to the specific needs and interests of statistics in developing countries.
You can choose between 3 specializations:
- Biostatistics
- Bioinformatics
- Quantitative Epidemiology
The specialization Data Science is not included in the ICP scholarship.
About studying in Hasselt
Why study at UHasselt?
Students from all over the world come to UHasselt to study the Master of Statistics and Data Science. Hasselt, located in the heart of the EU-region, is known for its hospitality, making international students feel right at home.
Did you know?
- UHasselt is ranked top 50 at Times Higher Education best universities under 50 years
- UHasselt has 15% international students from 75 different countries
New to Belgium?
Are you new to Belgium and still finding your way?
The Joint Organization of Statistical Scholars helps international students get around on campus and the city of Hasselt.
Where to find us?
- Campus Diepenbeek, building D
- Easy accessible by train, bike, bus and car
- 20 minute bike ride from Hasselt City center
Campus Diepenbeek
More info?
Peter Vandoren
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