Astronomy: Astronomy and Data Science
Structure of the programme
This 2-year programme focuses on the big-data aspects of both astronomy as a data-rich science and computer science. It prepares as much for a career in astronomy as in computer science, for careers in research as well as outside research, in academia or elsewhere in society. It consists of advanced Astronomy courses, two research projects in Astronomy, and selected courses from the Computer Science Master's programme. Students wanting to follow this specialisation must be proficient in programming, in particular in the Python language.
Programme (120 EC)
| Level | EC | |
|---|---|---|
| Electives | ||
| Astronomy Core Courses, at least | 500 | 18 |
| Instrumentation-related Astronomy Courses, at least | 400-500 | 6 |
| Astronomy Courses of any type | 400-500 | 12 |
| Mandatory Computer Science Courses | ||
| Databases and Data Mining | 500 | 6 |
| Advances in Data Mining | 500 | 6 |
| Neural Networks | 500 | 6 |
| Bayesian Networks | 500 | 6 |
| Research Projects | ||
| First Research Project | 500 | 30 |
| Master's Research Project | 600 | 30 |
Master Study Plan
At the start of the Master’s programme, students are required to draw up the Master Study Plan: a complete list of planned courses and projects for two subsequent academic years in consultation with the Study Advisor Astronomy. To select courses, students need to consult the course list for academic year 2016-2017 (to be added below), and/or the course list for academic year 2017-2018 (available in Spring 2017).
Learn more
For more information on the specific requirements of this specialisation, see the appendix of the Course and Examination Regulations