Minor Data Wise: Data Science in Society

Code for the minor: MIDW
Data plays an increasingly prominent role in public life. Scientists, journalists, and policy makers use of data-driven approaches to understand our society and to shape our daily activities. From sports to healthcare, from business to biology—artificial intelligence and data infrastructures are overwhelmingly present in all these spheres.
The minor Data Wise: Data Science in Society focuses on data science by giving students the theoretical and practical tools to evaluate, manage, and work with data. Specifically, it aims to increase student employability, since data science skills are not only increasingly listed as preferred in vacancies for university graduates, but also play a key role in the daily work of professionals across nearly all fields.
This minor is the result of a close collaboration between the Department of Sociology, Campus Fryslân, and the Centre for Information Technology. It brings together a diverse teaching team made up of experts from across the University of Groningen. Their combined expertise ensures that students are exposed to a broad range of perspectives on data, including its social, technical, and ethical dimensions.
Tailored to Interests
The minor combines a shared foundation with flexibility to suit your academic background. All students follow three mandatory courses that build core knowledge and collaborative skills. In addition, students can select three elective courses out of six—such as Introduction to programming, Data in practice, or Data visualization—to deepen their expertise in areas that match their interests.
Project-Based Learning
Interdisciplinarity, interaction, and awareness of real-world contexts are key to the kind of learning this minor promotes. At its core is a four-month group project based on real-world challenges provided by a variety of stakeholders in research, industry, and the public sector. Students can indicate their preferences from a curated list of twelve projects with external partners. By the end of the minor, they will be well prepared to work in teams with data scientists and contribute to the responsible and innovative use of data.
What Students Will Learn
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Understand how data practices shape society and influence our lives
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Gain conceptual and practical skills to collect, analyse, and report on data
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Learn to critically evaluate and actively participate in data-driven projects
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Be prepared to apply data science techniques within your own field of expertise
What Students Say
Psychology student Alexandros Christopoulos shares that the Data Wise minor helped him secure a bachelor thesis position working on a Motor Imagery Brain-Computer Interface—his dream project. Courses like Machine Learning, Introduction to Programming, and Data as Evidence gave him the tools and confidence to contribute meaningfully. He describes the minor as beneficial both personally and professionally, and says it inspired him to pursue a career in data science.
Requirements
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The minor is open to students from nearly all programmes and faculties across the university. However, due to significant content overlap with their existing programs, students from Computing Science (CS) and Artificial Intelligence (AI) are not eligible to enrol.
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The minor requires full-time availability and flexibility. Students cannot combine it with other courses and must be fully engaged with their collaborative data project.
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Two elective courses—Machine Learning and Data as Evidence—are taught at Campus Fryslân in Leeuwarden. Both are scheduled on the same day to reduce travel time.
Capacity
A maximum of 60 students can take part in this minor.
Deadlines
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Enrolment is possible from 23 May 2025 (10:00 CEST) up to 4 July 2025 (23:59 CEST)
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Signing up for electives: After you have been enrolled for the minor, you can enrol for the electives until August 31.
Sign up
Questions
For any questions, please email the programme coordinator, dr. Dario Rodighiero.
Course programme
Please see Ocasys for the course programme.
Mandatory courses
|
ECTS
|
Semester
|
---|---|---|
Introduction to data
(SOMINDW01) |
7,5
|
1a
|
Collaborative data project |
12,5 |
1a+1b
|
Dynamics of multi-disciplinary teamwork |
2,5 |
1a+1b
|
Elective courses
|
ECTS
|
Semester
|
Data as evidence |
2,5 |
1a
|
Introduction to programming |
2,5 |
1a
|
Opinion dynamics on the internet |
2,5 |
1a
|
Fundamentals of machine learning |
2,5 |
1a
|
Data in practice |
2,5 |
1a
|
Data visualization |
2,5 |
1a
|
Last modified: | 17 April 2025 12.14 p.m. |