Admission requirements - MSc Data Science for Food and Health
Interested in the master's programme Data Science for Food and Nutrition? Find out whether your knowledge and skills match the entry level of the programme.
This page describes the previous knowledge and skills required for admission to the Data Science for Food and Health programme specifically. For the additional general admission requirements of Wageningen University & Research, application deadlines and the application procedure, visit How to apply for a master's programme?
Are you interested in the programme, but not sure whether your background matches the stated requirements? Feel free to contact us.
Admission requirements
Required knowledge and skills
Purpose and reason for the admission requirements
The admission requirements for the master's programme Data Science for Food and Health are defined in such a way that the students should be able to successfully complete the programme nominally in two years. The programme teaches how to translate raw data into intelligible and actionable knowledge in the health and consumer sciences domain. Therefore, it is necessary that students have a solid basis in either health sciences, consumer sciences or data sciences to learn the interdisciplinary application with the other domains in the master’s. For collection and analyses of experimental data, applied knowledge of statistics and research methodology is necessary.
The criterion used for admission is
a WUR BSc degree in Nutrition and Health, Management and Consumer Studies, Health and Society, Communication and Life Sciences, or equivalent.
The norm for this equivalence is
An assessment of the candidate's expertise in one or more of the following three domains:
- Health sciences
- Consumer sciences
- Computer sciences and/or Data sciences
Additionally, the candidate should have sufficient knowledge on:
- Research methodology
- Statistics
Not all topics mentioned need to be mastered at the same level; they will be weighed by the Admission Board per individual application.
Method of assessment whether this norm is met
- Transcript of records displaying the content of previous course subjects and project work;
- Curriculum vitae displaying relevant work, internship and/or project experience on an academic level in a relevant field if applicable.
Scores attributed by the Admission Board
Admitted / not admitted / admitted under condition obtaining the BSc or MSc degree / not admitted with offer of pre-master
Compensation of knowledge gaps
The Admission Board may allow and/or suggest compensation of knowledge gaps by:
- a GPA≥7.0* for the previous education for small discrepancies as new knowledge is sufficiently easily acquired;
- a GPA≥7.0* and an individual pre-master's programme for larger discrepancies that can be compensated in ≤30 ECTS and one year of study.
*Check the general admissions page for the International credentials evaluation guide for international equivalencies to a Dutch GPA>7.0. This guide includes compensating factors for a slightly lower GPA the Admission Board may include in their judgement.
Contact us through the contact button above to discuss the possibilities of a pre-master or how to mitigate knowledge gaps if you are still in the process of obtaining your degree.
Find out more about enrolment and fees of a pre-master's programme.
Additional context for admission
Admissible study programmes
Study programmes of which the graduates may meet the knowledge requirements of Data Science for Food and Health are for example: Nutrition, Consumer Science, Health, Food Science & Nutrition, Computer Sciences, Data Sciences and Biomedical Sciences.