Find the programme structure that fits your year of admission on your Study Information.
The structure of the programme is very free. You can choose from a large number of restricted elective and elective courses to compose the programme as you choose. The courses offered seek to couple mathematical, statistical, and practical aspects, usually with a focus on a special type of study and the theoretical, and practical problems it entails.
You may choose to focus on one of the three disciplines (probability theory, theoretical statistics or data processing) and become, for example, a probability theoretician or obtain skills in statistical computing.
There are good opportunities for participating in external projects as part of your studies. You can also choose to collaborate with a company or an institution by doing a project in practice.
Furthermore, it is possible to study abroad during your programme. You can choose to study for one or two semesters or for a shorter period, for instance attend a summer school course.
The programme concludes with a thesis, where you work in depth with an academic problem. Often, the thesis has a practical point of departure, where the solution to the problem may of importance to many people.
Here are some examples of thesis topics:
- Survival Analysis - Analysis of Waiting Times
- Ruin Problems
- Markov Chain Monte Carlo Methods
- Cointegration - Stable Correlations in Explosive Processes
- Missing data - When It Is Informative that Data Is Missing
Compulsory courses: 30 ECTS
Restricted elective courses: 30 ECTS
Elective courses: 30 ECTS
Master's thesis: 30 ECTS
|Block 1||Block 2||Block 3||Block 4|
|Year 1||Restricted elective course||Restricted elective course||Restricted elective course||Restricted elective course|
|Regression||Statistics A||Statistics B||Project in Statistics|
|Year 2||Elective course||Elective course||Thesis|
|Elective course||Elective course|
One block each year equals nine weeks of study and 15 ECTS.
Restricted Elective Courses
Choose your restricted elective courses from the lists below. Click on each course for a detailed description.
- Advanced Probability Theory 1
- Computational Statistics
- Advanced Vector Spaces
- Econometrics 2: Statistic Analysis of Econometric Time Series
- Advanced Topics in Machine Learning
- Monte Carlo Methods in Insurance and Finance
- An Introduction to Large Deviations (the course is not offered in the academic year 2022/23)
- Advanced Vector Spaces
- Demography and Mortality
- Machine Learning A
- Seminar in Statistics
- Introduction to Extreme Value Theory (the course is not offered in the academic year 2022/23)
- Advanced Probability Theory 2
- Survival Analysis (the course is not offered in the academic year 2022/23)
- Optimization in Data Science (the course is not offered in the academic year 2022/23)
- Functional Analysis
- Geometry 2
- Machine learning B
- Point Processes
- Numerical Optimization
- Semiparametric Inference
- Machine Learning Methods in Non-Life Insurance
- Applied Probability
- Topics in Statistical Genetics (the course is not offered in the academic year 2022/23)
- Differential Operators and Function Spaces (DifFun)
- Models for Complex Systems (ModComp)
- Applied Programming
- Mathematical Models in Epidemiology
- Online and Reinforcement Learning (OReL)
- Advanced Deep Learning (ADL)