Structure of the Master Specialisation Data Science
The list below illustrates the basic organization of the 120 ec Data science master specialisation, 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 programme is in principle structured in the following manner.
The components are further refined as follows:
Specialisation basis (mandatory courses) (18 ec):
- NWI-I00041 Information Retrieval (6 ec)
- NWI-IMC030 Machine Learning in Practice (6 ec)
- NWI-IMC012 Bayesian Networks (6 ec)
Specialisation electives (24 ec):
to be chosen from the categories below (not necessarily all from the same category or one from all categories).
Data Science Theory and Tools
- NWI-IMC056 Statistical Machine Learning (6 ec)
- NWI-IMC042 Natural Computing (6 ec)
- NWI-NM048D CDS: Machine Learning (3 ec)
- NWI-NM048B: Advanced Machine Learning (6 ec)
Data Science Applications
- NWI-IMC037 Intelligent Systems in Medical Imaging (6 ec)
- SOW-MKI49 Neural Information Processing Systems (6 ec)
- NWI-SM299 Pattern Recognition for Natural Sciences (3 ec)
- LET-REMA-LCEX06 Text and Multimedia Mining (6 ec)
- LET-REMA-LCEX10 (Automatic) Speech Recognition (6 ec)
- NWI-NM116 Machine Learning in Particle Physica and Astronomy (3 ec)
- SOW-MKI52 New Media Lab (6 ec)
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 Radboud University, but overlap with other courses is not allowed. Courses from the master Computing Science are eligible by default. Should be approved 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.
| 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).|