Master’s in Data Science for Food and Health

The Master's in Data Science for Food and Health is a two-year programme. During the two years, you work towards a complete repertoire of expertise and skills needed to become fully accomplished integrators. Check the programme Study Handbook for more in-depth information about learning outcomes and a complete list of all courses.

In the first year you will decide which track within the Master you want to follow. These track focus on Data Science combined with one of the following domains within WUR:  

• Nutrition and Health 
  Work with large datasets from health trackers, clinical trials, or epidemiological studies. Learn to apply data science methods to investigate complex nutrition and health questions.
• Consumer Behavior 
  Learn to analyse marketing and behavioral data, such as eye-tracking patterns, purchasing behavior, and demographic trends. Explore how AI and recommendation systems can be applied to better understand consumer decisions.
• Lifestyle and Health
  • Data science for healthy lifestyles: Focus on understanding and promoting sustainable, healthy behaviors. Learn about behavioral change, intervention strategies, and how data science supports these efforts.
  • Data science for population health: Use data from social media, networks, communities, and public policy to study and improve health at the population level.
• Food Technology 
  Combine data from chemical, microbiological, and physical analyses with consumer, epidemiological, and socio-economic data. Apply data science to questions related to food quality, safety, sustainability, and consumer preferences. 

Based on your chosen track, you can personalize the program by following course such as: 

• Compulsory courses, like an introductory course (6 EC) and Statistics for Data Scientist (6 EC) to ensure you start with a sound theoretical basis.  
• Courses chosen based on your background to get basic knowledge of the domain or Data Science (6-18 EC)
• A personalised programme of 18 EC (three courses of 6 EC) to deepen your domain knowledge and broaden your horizon about different data types.  
• Academic Consultancy Training and Data Science Ethics: to master professional skills in an interdisciplinary setting.  

• Major thesis (36 credits): conduct your own research project at one of WUR's research groups where you combine the Data Science and domain knowledge.
• Internship (24 credits): gain experience at a company in the field of Data Science and the domain of your choice. 

While there are no pre-defined specialisations, students can follow various tracks based on their interests. For a more detailed information on the programme structure, read the Study Handbook.

What to expect from the programme:

• Lectures – A lecturer explains key concepts and course material during classroom sessions.
• Tutorials – You’ll work individually or in small groups to complete guided assignments.
• Lab sessions – Primarily computer-based, where you practise using economic and statistical models.
• Problem-Based Learning (PBL) – You collaborate with fellow students and a supervisor to analyse and solve real-world case studies.
• Self-study – Time for independent study is built into your timetable, but you’re also free to organise it flexibly outside scheduled hours.

At WUR, personal guidance and connection are a key part of the student experience. That’s why we offer more support than most other Dutch universities, with a strong team of lecturers, study advisers, and student counsellors ready to help you succeed. With the personal attention and involvement of the study adviser a tailored programme can be made, which meets your ambitions and interests.  

This master's is unique, as it is the only master's programme with Data Science within WUR. This programme can also be combined with other masters within WUR to deepen your knowledge about the WUR domains. You can always contact us to explore the double degree option.

Would you like to compare the Master’s in Data Science for Food and Health? Check the possibilities on Studiekeuze123.nl.

Upon graduating as a data scientist specialising in Food and Health, you will possess robust foundational knowledge alongside excellent interpersonal skills. These attributes are symbolic for the pi-shaped professional model: a versatile expert, well-versed in two domains. Your training will encompass the art of intertwining and harmonizing these two realms. With a pi-shaped foundation, graduates of the Data Science for Food and Health programme are equipped to embrace diverse roles within an organization and excel as adept bridge builders. This versatility makes you well-suited for collaborative work within multidisciplinary teams, enabling you to assume your role in society and the professional sphere as a next-generation data scientist. 

Student Career Services facilitates WUR students towards the labour market. If you need help in your orientation towards your future career. 

Interested in the master's programme Data Science for Food and Health? Find out whether your knowledge and skills match the entry level of the programme.

Purpose and reason for the admission requirements

The admission requirements for the master's programme Data Science for Food and Health are defined such that the student should be able to successfully complete the programme in two years, the nominal duration of the programme.  

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 one of the domains (food, nutrition, health, consumer) and/or data sciences.  

For collection and analyses of experimental data, good knowledge of statistics and research methodology is necessary.  

The criterion used for admission is

a Wageningen bachelor's degree in Nutrition and Health, Food Technology, 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 domains:  

• Food and Nutrition sciences  
• 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 of obtaining the BSc or MSc degree / not admitted with offer of pre-master.

Admissible study programmes

Study programmes of which the graduates maymeet 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.

You can apply for this Master's here.

The Admission Board may allow and/or suggest compensation of knowledge gaps by:  

• a GPA≥7.0* for the previous Bachelor's programme 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. The pre-master's needs to be completed successfully to be allowed to start with the master's programme.  

*Check the Application & Admission page for the International credentials evaluation guide for international equivalencies to a Dutch GPA>7.0. The Admission Board may include compensating factors for a slightly lower GPA in their judgement.  

Contact us to discuss the possibilities of a pre-master's or how to mitigate knowledge gaps if you are still in the process of obtaining your degree.  

Studying comes with a cost. Want to know what kind of expenses to expect? All information about the costs of this programme can be found on this page. 

There’s more to student life than just studying! Whether it's living together, dancing at student parties, discovering cosy cafés, or joining one of the many active associations, Wageningen has something for everyone. The town is full of energy, with festivals, quirky sports clubs, and fun events happening all year round. Additionally, there are parks, forests, and a river nearby, so if you enjoy the outdoors, you're in the right area. You’ll find everything you need to know on this page.