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About us Faculty of Behavioural and Social Sciences Education BSS Minor

Minor Data Wise: Data Science in Society

Minor Data Wise: data science in society
Minor Data Wise: Data Science in Society

Code: MIDW

Data plays an increasingly prominent role in society. Scientists, journalists, politicians, policy makers, and governmental institutions all make use of ‘big data’ and ‘data-driven approaches’ to understand our society and to shape our daily lives. From sports to healthcare, from business to biology—data and data infrastructures are overwhelmingly present in all these spheres.

The minor 'Data Wise: data science in society' focuses on knowledge about data and on skills to critically evaluate, shape and work with data. Specifically, it will improve the students’ employability since data science skills are increasingly listed as requirement or preferred skills in vacancies for university graduates. Furthermore, nearly all professionals need to have affinity with data and related processes in the course of their work.

This minor arises from a collaboration between Sociology, Centre for Information Technology and Campus Fryslân. The teaching team is made up of experts from across the University of Groningen and UMCG. Download our flyer here.

Due to the Data Wise minor, I was able to secure a position for my bachelor thesis in a Motor Imagery Brain-Computer Interface, my dream job! Courses such as Machine learning, Intro to Programming and Data as Evidence gave me tools and confidence to get involved with my project. The minor was beneficial for me as a person and for my career, as I now plan for a career in data science.
— Alexandros Christopoulos, psychology student

Interdisciplinary, project-based learning

Because interdisciplinarity, interaction and awareness of real-world contexts are key to the kinds of learning needed, the core of the minor is a group project on which students work for a period of four months. These real-world projects come from a diversity of stakeholders from research, business, government or civil society. By the end of the minor, students will have a highly desirable profile: team players who are able to collaborate with data scientists, making real contributions to responsible and innovative use of data.

Students who complete the minor will

  • understand how data practices influence our lives, positively and negatively, and shape society
  • acquire the conceptual and practical skills to collect, analyze, and report on this potentially enormous source of information and to do their work responsibly
  • critically evaluate and participate in “big data”/data-driven projects
  • be able to pursue their careers in settings where data and data infrastructures intersect with their domain expertise and activities

Requirements

  • There are no pre-requisites and we welcome students from almost all programmes and all faculties across the university
  • Note!: Students from the programme "Artificial Intelligence" (AI) are excluded from this minor because the AI courses and the minor courses overlap too much
  • The minor requires a lot of availability and flexibility, because of its project-based learning. This means that it is not possible to follow other courses outside the data wise minor and students need to be available to follow the minor full time to fully engage with their project team and with the external project partner

Sign up

  • Due to significant content overlap with our existing program, students from Computing Science (CS) and Artificial Intelligence (AI) are currently ineligible to enroll in the Data Wise minor.
  • The enrollment window is open from May 24 (at noon) until July 5.
  • Discover more about our minors at the Minors Market on Thursday, May 23, 2024, from 11:30 a.m. to 1:30 p.m.

Courses

A maximum of sixty students can take part in the minor. Enrolled students must follow three mandatory courses and three elective courses (a maximum of thirty can take part in each elective). Students must enrol in the entire program, as it is not possible to enrol for individual courses.

All detais regarding course are available in Ocasys.

Courses
ECTS
Frequency
Semester
Introduction to Data
(SOMINDW01)
7,5
mandatory
1a

Collaborative Data Project
(SOMINDW02)

12,5

mandatory

1a+1b

Dynamics of multi-disciplinary teamwork
(SOMINDW03)

2,5

mandatory

1a+1b

Data as evidence
(SOMINDW04)

2,5

elective

1a

Introduction to Programming
(SOMINDW05)

2,5

elective

1a

Opinion dynamics on the internet
(SOMINDW06)

2,5

elective

1a

Fundamentals of Machine Learning: Theory and Practice
(SOMINDW07)

2,5

elective

1a

Data in Practice. A journey through the whole data life cycle
(SOMINDW08)

2,5

elective

1a

Data visualization
(SOMINDW09)

2,5

elective

1a

Questions?

Contact: datawise rug.nl

Last modified:18 March 2024 11.41 a.m.