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 2024.
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 courses for all tracks
Conditionally elective courses for all tracks
Optional courses
- Visualization (DD2257) 7.5 credits
- Methods in High Performance Computing (DD2356) 7.5 credits
- Advanced Computation in Fluid Mechanics (DD2365) 7.5 credits
- Machine Learning (DD2421) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Mathematical Modelling of Biological Systems (DD2435) 9.0 credits
- Advanced Algorithms (DD2440) 6.0 credits
- Complexity Theory (DD2445) 7.5 credits
- Foundations of Analysis (SF1677) 7.5 credits
- Groups and Rings (SF1678) 7.5 credits
- Complex Analysis (SF1691) 7.5 credits
- Optimization (SF1811) 6.0 credits
- Numerical Solutions of Differential Equations (SF2521) 7.5 credits
- Numerical algorithms for data-intensive science (SF2526) 7.5 credits
- Project Course in Scientific Computing (SF2567) 7.5 credits
- Financial Mathematics, Basic Course (SF2701) 7.5 credits
- Applied Nonlinear Optimization (SF2822) 7.5 credits
- Geometric Control Theory (SF2842) 7.5 credits
- Optimal Control Theory (SF2852) 7.5 credits
- Applied Systems Engineering (SF2866) 7.5 credits
- Regression Analysis (SF2930) 7.5 credits
- Modern Methods of Statistical Learning (SF2935) 7.5 credits
- Portfolio Theory and Risk Management (SF2942) 7.5 credits
- Time Series Analysis (SF2943) 7.5 credits
- Computer Intensive Methods in Mathematical Statistics (SF2955) 7.5 credits
- Topological Data Analysis (SF2956) 7.5 credits
- Martingales and Stochastic Integrals (SF2971) 7.5 credits
- Financial Derivatives (SF2975) 7.5 credits
- Risk Management (SF2980) 7.5 credits
- Computational Fluid Dynamics (SG2212) 7.5 credits
- Applied Computational Fluid Dynamics (SG2224) 5.0 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.
Conditionally elective courses for all tracks
Optional courses
- Visualization (DD2257) 7.5 credits
- Machine Learning (DD2421) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Mathematical Modelling of Biological Systems (DD2435) 9.0 credits
- Advanced Algorithms (DD2440) 6.0 credits
- Complexity Theory (DD2445) 7.5 credits
- Optimization (SF1811) 6.0 credits
- Program Construction in C++ for Scientific Computing (SF2565) 7.5 credits
- Project Course in Scientific Computing (SF2567) 7.5 credits
- Optimal Control Theory (SF2852) 7.5 credits
- Applied Systems Engineering (SF2866) 7.5 credits
- Modern Methods of Statistical Learning (SF2935) 7.5 credits
- Portfolio Theory and Risk Management (SF2942) 7.5 credits
- Topological Data Analysis (SF2956) 7.5 credits
- Statistical Machine Learning (SF2957) 7.5 credits
- Financial Derivatives (SF2975) 7.5 credits
- Risk Management (SF2980) 7.5 credits