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Structure of the Master Specialisation Data Science

Dear student,

We are working on solutions for hybrid education that will take place online and on campus. Therefore the instructional modes, number of exams, the form of the exams and/or assignments may change. You will be informed through Brightspace in case of changes. The course information in the Course guide provides an indication of what you can expect in the course.

In the case of not being able to attend one or more practical courses/lab days due to corona measures, the course coordinator will decide if the student is obligated to re-take the missed meeting and how this will take place.
The list below illustrates the basic organization of the 120 ec Data science master specialisation,[1] which consists of the following elements:

  • Specialisation basis (18 ec)
  • Specialisation electives (24 ec)
  • Specialisation specific research seminar (6 ec)
  • Research internship (15 ec)
  • Master electives (18 ec)
  • Computer science and society (3 ec)
  • Free electives (6 ec)
  • Master thesis project (30 ec)

The components are further refined as follows:

Specialisation basis (mandatory courses) (18 ec):

Specialisation electives (24 ec):

to be chosen from the courses below:

Data Science Theory and Tools

Data Science Applications

Data Science Aspects

Specialisation specific research seminar (6 ec)

Research internship (15 ec)
See this page for additional information.

Master electives (18 ec)
To be chosen from master courses offered by the master Computing Science or Artificial Intelligence, provided that there is no overlap with other courses of the programme. Master courses from other programmes are subject to approval by the Examining Board.

Computer, Science and Society (3 ec)

Free electives (6 ec)
To be chosen from courses offered by Radboud University, but overlap with other courses is not allowed. Should be approved by the Examining Board.

Final thesis (30 ec): MSc-project.

The final thesis is scheduled in the last semester. The MSc project is finished by writing a Master's thesis. Generally speaking, students will do their Master's project under the supervision of a member of staff of their own university. However, students may, after consulting a local supervisor, choose to do a Master's project at another site, or an external project at a company or abroad.

The total amount of ec's of this programme should be 120 ec at least.

[1] The programme described here is the research specialisation Data Science. Students who are more interested in taking a more applied and/or management related angle may have a look at the societal specialisations Science, Management and Innovation or Science in Society, which can also be taken with a Data Science programme (see the master-specific requirements for Computing Science at the bottom of these respective pages).