Each themed elective package consists of a number of elective courses and projects, which we recommend you choose from if you wish to specialise in the relevant research area.
To the extent possible, we aim to ensure that courses within the same themed elective package do not overlap in times of classes if you follow the recommended course of study within the standard time limits.
Computational Science is a branch of mathematics that deals with efficient numerical solutions to mathematically formulated models. This could be, for example, optimising a financial portfolio, calculating the flow of air around a car, or weather forecasts.
Please note that some of the recommended courses may not be offered every year.
Autumn
We recommend that you choose MM834: Partial differential equations: theory, modelling and simulation (10 ECTS) if you haven't already passed an equivalent course as part of your Bachelor's degree.
Additionally, we recommend the following course:
- DM871: Linear and Integer Programming (5 ECTS)
- DM872: Mathematical Optimization at Work (5 ECTS)
- MM802: Stochastic differential equations I (10 ECTS)
- MM831: Differential equations II (5 ECTS)
- MM836: Convex analysis (5 ECTS)
Spring
Please note that some of the recommended courses may not be offered every year.
Autumn
We recommend that you choose MM835: Probability theory (10 ECTS) if you haven't already passed an equivalent course as part of your Bachelor's programme.
Additionally, we recommend the following courses:
- MM802: Stochastic Differential Equations I (10 ECTS)
- ST813: Statistical modelling (10 ECTS)
- ST821: Time Series (5 ECTS)
Spring
- ST803: Extreme value statistics (5 ECTS)
- ST811: Multivariate statistical analysis (5 ECTS)
- ST816: Computational Statistics (10 ECTS)
- ST817: Mathematical Statistics II (5 ECTS)
- ST818: Insurance Statistics (5 ECTS)
Some of the recommended courses may not necessarily be offered every year.
Autumn
- DM841: Heuristics and Constraint Programming for Discrete Optimization (10 ECTS)
- DM864: Advanced Data Mining (5 ECTS)
- DM873: Deep Learning (10 ECTS)
- ST813: Statistical Modelling (10 ECTS)
- ST821: Time Series (5 ECTS)
Spring
- DM846: Logic for Computer Science (10 ECTS)
- DM870: Data mining and machine learning (10 ECTS)
- DM871: Linear and Integer Programming (5 ECTS)
- DM872: Mathematical Optimization at Work (5 ECTS)
- DM879: Artificial Intelligence (10 ECTS)
- ST811: Multivariate Statistical Analysis (5 ECTS)
- ST817: Mathematical Statistics II (5 ECTS)