Data Science Minor (2024-2025)

Data plays a role in almost every scientific discipline, business and industry, and social organisations. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour, marketeers analyse the online behaviour of visitors of websites and online services, linguists discover patterns in languages. And of course, businesses like Google and Amazon are shifting user preference data to fulfill desires we do not even know we have. In this minor, you will get acquainted with data and data structures and develop insights into how data is turned into knowledge and solutions, with the help of computers.

About the minor

You will follow at least 15 ECs worth of Data Science courses that are not already part of your compulsory bachelor curriculum. These ECs consist of one obligatory course and multiple electives. All minor students follow the 6 EC course Data Science Project (NWI-IBC045, taught in Semester 2) and construct their own minor by choosing electives. The courses you can choose depend on your current curriculum. Some courses are more suitable if you have a technical background, for example, because you study at the Faculty of Science (FNWI) or your bachelor is in Artificial Intelligence. Otherwise, you can follow a less technical track. Both groups of courses are listed below. 

You can register for the minor (course code NWI-MI-DATSC) starting July 15th. Please note that you also need to enroll in each of the individual courses that you plan to follow as part of the minor.

This minor is only available to students at Radboud University. For HBO students of computer science, the university’s Faculty of Science offers a different Data Science minor, please visit www.kiesopmaat.nl/modules/run/NWI/140663/ or contact Perry Groot (Perry.Groot [at] science.ru.nl (Perry[dot]Groot[at]science[dot]ru[dot]nl)) for more information.

Admission

All bachelor students can apply, except for those studying Computing Science with a specialisation in Data Science.

Note that:

  • If your curriculum does not contain mathematics, Mathematics for Data Science as part of the DS minor is obligatory. Classes for this course will be scheduled after consulting with the students, to maximize possible attendance.
  • If your curriculum does not contain statistics, an introductory statistics course as part of the DS minor is obligatory.
  • If your curriculum does not contain a programming course, an introductory programming course as part of your DS minor is obligatory.
  • Important exception! If your curriculum does not contain mathematics, no statistics, and no programming (i.e., all three points above apply), then you need to choose only two of the three obligatory courses (Mathematics for Data Science, an introductory statistics course, an introductory programming course).

See below for the recommended courses and available electives.

Programming courses

Faculty

Bachelor

Recommended

Alternative(s)

Faculty of ScienceBiologyIntroduction to R programming in BiologyAdvanced data analysis and programming
Faculty of Arts,
Faculty of Law,
Faculty of Philosophy, Theology and Religious Studies
AllProgramming for beginners: Python
Faculty of Social Science,
Nijmegen School of Management
AllProgramming 1 
Faculty of Medical SciencesMedicine Advanced data analysis and programming 
DentistryAdvanced data analysis and programming 

Statistics courses

Faculty

Bachelor

Recommended

Alternative(s)

Faculty of ScienceComputing ScienceStatistics 1Statistics (Dutch)
Physics and AstronomyStatistics (Dutch)Statistics 1
Faculty of ArtsDutch Language and CultureStatistics (Dutch)
OtherStatistics
Faculty of Philosophy, Theology and Religious StudiesAllStatistics
Faculty of LawAllStatisticsResearch and Intervention Methodology B (Dutch)
Faculty of Medical SciencesDentistryContext, science and innovation (Dutch)Statistics 1

Electives

Technical track
 

Course

   P1   

   P2   

   P3   

   P4  

Introduction to Machine Learning                            3 EC  🟥   
Information Modelling and Databases                    6 EC  🟥  🟥  
Data Mining                                                                  6 EC  🟥  🟥  
Data Science with Applications for Medicine and Biology 
                                                                                             6 EC
  🟥  🟥  
Data: Structural Bioinformatics                                 3 EC   🟥  
Genomics and Big Data                                              6 EC    🟥 
Signal analysis and MATLAB                                       4 EC    🟥 
Big Data                                                                         6 EC    🟥  🟥
Deep Learning                                                              6 EC    🟥  🟥
Image Analysis                                                              3 EC     🟥

Non-technical track
 

Course

   P1   

   P2   

   P3   

   P4   

Digital media technology  (Dutch)                             5 EC  🟥     
Data Culture                                                                  5 EC  🟥   
Introduction to Digital Economics and FinTech      6 EC   🟥   
Linguistic Databases  (Dutch)                                     5 EC  🟥  🟥  
Societal Impact of AI                                                    6 EC  🟥  🟥  
Social Media and New Media                                     5 EC    🟥 
IT and Society                                                                3 EC    🟥 
Information Science                                                     5 EC    🟥  🟥
Artificial Intelligence in Action                                    5 EC    🟥  🟥
Law, Privacy and Identity                                             3 EC     🟥

Contact information

If you want to include a course that is not listed, or need more advice regarding possible electives, please contact the minor coordinator Stefan Frank (minordatascience [at] ru.nl (minordatascience[at]ru[dot]nl))

Organizational unit
Radboud AI