Mathematics of Data Science | Courses

The specialisation in Mathematics of Data Science comprises 2 years of study for a total of 120 EC.

Year 1

In the first year you will gather 60 EC, spread out over courses in three categories:

Compulsory basic courses
The compulsory courses for the specialisation in Data Science are:
- Continuous Optimization (6 EC)
- Data Science (5 EC)
- Deep Learning – From Theory to Practice (5 EC)
- Pioneers of Applied Mathematics (5 EC)
- Scientific Computing (6 EC)
The above courses combined cover 27 EC. You will collect the remaining 33 EC for year 1 by following at least 3 advanced courses, to be complemented by your choice of elective courses.
Advanced courses
- Complex Networks (5 EC)
- Discrete Optimisation (5 EC)
- Information Theory and Statistics (5 EC)
- Markov Decision Theory and Algorithmic Methods (5 EC)
- Random Signals and Filtering (5 EC)
- Spatial Statistics (5 EC)
Recommended elective courses
- Basic Machine Learning (5 EC)
- Game Theory (5 EC)
- Image Processing and Computer Vision (5 EC)
- Inverse Problems in Imaging (8 EC)
- Managing Big Data (5 EC)
- Probabilistic Programming (5 EC)
- Time Series Analysis (5 EC)

Year 2

The second year of the specialisation in Data Science specialisation consists of a compulsory internship (20 EC) and your master's assignment (40 EC).

Your internship
As an intern you will work in an environment relevant to your future as a professional. Suitable internships are available in, e.g.:
- companies that are centred around the use of data, like Booking.com, Uber, or Google.
- tech companies like Philips or Thales that are using new developments in data science to improve their products
- governmental organisations
Apart from the above, an internship with a foreign university is also a possibility. Based on what you wish to learn and how you see your future, you and your coordinator together will determine the choice that best suits your situation and preferences.