Courses for Applied and Computational Mathematics
The two-year master's programme in Applied and Computational Mathematics consists of three terms of courses and one final term dedicated to the master's degree project. Each term consist of approximately 30 ECTS credits. Depending on which track you choose, you will study different courses. The courses presented on this page apply to studies starting in autumn 2026.
Year 1
At least one of the conditionally elective courses SF2832, SF2863 and SF2812 among the general courses has to be studied, and also minimum one of the courses SF2527 and SF2524.
The conditionally elective courses can be studied during the first or second year.
Students from CTMAT who has taken SF1693 cannot take SF2527, and can choose to take SF2524 or not.
Mandatory SF2940 can be replaced by SF2944 (note: only one can be taken within the TTMAM programme).
Mandatory courses for all tracks
Conditionally elective courses for all tracks
Optional courses
- Visualization (DD2257) 7 credits
- Machine Learning, Advanced Course (DD2434) 7 credits
- Mathematical Modelling of Biological Systems (DD2435) 9 credits
- Advanced Algorithms (DD2440) 6 credits
- Optimization (SF1811) 6 credits
- Optimal Control Theory (SF2852) 7 credits
- Applied Systems Engineering (SF2866) 7 credits
- Modern Methods of Statistical Learning (SF2935) 7 credits
- Portfolio Theory and Risk Management (SF2942) 7 credits
- Topological Data Analysis (SF2956) 7 credits
- Financial Derivatives (SF2975) 7 credits
- Risk Management (SF2980) 7 credits
- Methods in High Performance Computing (DD2356) 7 credits
- Advanced Computation in Fluid Mechanics (DD2365) 7 credits
- Machine Learning (DD2421) 7 credits
- Foundations of Analysis (SF1677) 7 credits
- Groups and Rings (SF1678) 7 credits
- Complex Analysis (SF1691) 7 credits
- Numerical algorithms for data-intensive science (SF2526) 7 credits
- Financial Mathematics, Basic Course (SF2701) 7 credits
- Applied Nonlinear Optimization (SF2822) 7 credits
- Geometric Control Theory (SF2842) 7 credits
- Regression Analysis (SF2930) 7 credits
- Time Series Analysis (SF2943) 7 credits
- Computer Intensive Methods in Mathematical Statistics (SF2955) 7 credits
- Martingales and Stochastic Integrals (SF2971) 7 credits
- Computational Fluid Dynamics (SG2212) 7 credits
- Applied Computational Fluid Dynamics (SG2224) 5 credits
- Deep Generative Models and Synthesis (DD2601) 7 credits
- Algorithms and Complexity (DD2352) 7 credits
Year 2
At least one of the conditionally elective courses SF2832, SF2863 and SF2812 among the general courses has to be studied, and also minimum one of the courses SF2527 and SF2524.
The conditionally elective courses can be studied during the first or second year.
Students from CTMAT who has taken SF1693 cannot take SF2527, and can choose to take SF2524 or not.
Mandatory SF2940 can be replaced by SF2944 (note: only one can be taken within the TTMAM programme).
Conditionally elective courses for all tracks
Optional courses
- Visualization (DD2257) 7 credits
- Machine Learning (DD2421) 7 credits
- Machine Learning, Advanced Course (DD2434) 7 credits
- Mathematical Modelling of Biological Systems (DD2435) 9 credits
- Advanced Algorithms (DD2440) 6 credits
- Complexity Theory (DD2445) 7 credits
- Optimization (SF1811) 6 credits
- Program Construction in C++ for Scientific Computing (SF2565) 7 credits
- Optimal Control Theory (SF2852) 7 credits
- Applied Systems Engineering (SF2866) 7 credits
- Modern Methods of Statistical Learning (SF2935) 7 credits
- Portfolio Theory and Risk Management (SF2942) 7 credits
- Topological Data Analysis (SF2956) 7 credits
- Statistical Machine Learning (SF2957) 7 credits
- Financial Derivatives (SF2975) 7 credits
- Risk Management (SF2980) 7 credits
- Deep Generative Models and Synthesis (DD2601) 7 credits