The following courses are part of study year two.
The course application codes and study periods are valid for the academic year 2025/2026. For other academic years, different application codes and study periods may apply
General Courses
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
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2832 Mathematical Systems Theory | 51194 | 7.5 credits | 7.5 | |||
| SF2863 Systems Engineering | 50594 | 7.5 credits | 7.5 | |||
| SF2812 Applied Linear Optimization | 60860 | 7.5 credits | 7.5 | |||
| SF2524 Matrix Computations for Large-scale Systems | 7.5 credits | |||||
| SF2527 Numerical Methods for Differential Equations I | 7.5 credits |
Optional courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| DD2257 Visualization | 50373 | 7.5 credits | 7.5 | |||
| DD2445 Complexity Theory | 50474 | 7.5 credits | 7.5 | |||
| SF2852 Optimal Control Theory | 51220 | 7.5 credits | 7.5 | |||
| SF2866 Applied Systems Engineering | 50555 | 7.5 credits | 7.5 | |||
| SF2935 Modern Methods of Statistical Learning | 51320 | 7.5 credits | 7.5 | |||
| SF2942 Portfolio Theory and Risk Management | 51830 | 7.5 credits | 7.5 | |||
| SF2956 Topological Data Analysis | 50308 | 7.5 credits | 7.5 | |||
| SF2975 Financial Derivatives | 51850 | 7.5 credits | 7.5 | |||
| DD2435 Mathematical Modelling of Biological Systems | 50358 | 9.0 credits | 6.0 | 3.0 | ||
| DD2440 Advanced Algorithms | 50303 | 6.0 credits | 1.5 | 4.5 | ||
| SF2565 Program Construction in C++ for Scientific Computing | 51541 | 7.5 credits | 3.5 | 4.0 | ||
| DD2434 Machine Learning, Advanced Course | 50325 | 7.5 credits | 7.5 | |||
| SF1811 Optimization | 50285 | 6.0 credits | 6.0 | |||
| SF2957 Statistical Machine Learning | 51680 | 7.5 credits | 7.5 | |||
| SF2980 Risk Management | 51833 | 7.5 credits | 7.5 | |||
| DD2421 Machine Learning | 60242 | 7.5 credits | 7.5 | |||
| SF2567 Project Course in Scientific Computing | 7.5 credits |
Specialisations
Track, Computational Mathematics (COMA)
Courses (COMA)
Mandatory courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF250X Degree Project in Scientific Computing, Second Cycle | 61555 | 30.0 credits | 15.0 | 15.0 |
Minimum 4 conditionally elective trackcourses must be studied during year 1 and 2.
Conditionally elective courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2529 Inverse Problems | 52095 | 7.5 credits | 7.5 | |||
| SF2527 Numerical Methods for Differential Equations I | 51861 | 7.5 credits | 3.0 | 4.5 | ||
| SF2565 Program Construction in C++ for Scientific Computing | 51541 | 7.5 credits | 3.5 | 4.0 | ||
| SF2524 Matrix Computations for Large-scale Systems | 51842 | 7.5 credits | 7.5 |
Track, Mathematics of Data Science (DAVE)
Courses (DAVE)
Compulsory courses on the track (15 cr) + conditionally elective courses (15 cr) = 30 cr.
Mandatory courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2935 Modern Methods of Statistical Learning | 51320 | 7.5 credits | 7.5 | |||
| SF290X Degree Project in Mathematical Statistics, Second Cycle | 61556 | 30.0 credits | 15.0 | 15.0 |
At least two conditionally elective courses has to be studied on the track. *One of the conditionally elective courses on the track has to be SF2930 or SF2943.
Conditionally elective courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2529 Inverse Problems | 52095 | 7.5 credits | 7.5 | |||
| SF2956 Topological Data Analysis | 50308 | 7.5 credits | 7.5 | |||
| SF2957 Statistical Machine Learning | 51680 | 7.5 credits | 7.5 |
Track, Financial Mathematics (FMIA)
Courses (FMIA)
At least 30 cr need to be studied on the track: 15 cr compulsory courses + 15 cr of the conditionally elective courses.
Mandatory courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2942 Portfolio Theory and Risk Management | 51830 | 7.5 credits | 7.5 | |||
| SF291X Degree Project in Financial Mathematics, Second Cycle | 61557 | 30.0 credits | 15.0 | 15.0 |
Among the conditionally elective courses at least one course from each year has to be studied. However in year 1 either SF2930 or SF2943 has to be studied. Note that if you plan to study SF2975 in year 2 it is strongly recommended to study SF2971 in year 1.
Conditionally elective courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2975 Financial Derivatives | 51850 | 7.5 credits | 7.5 | |||
| SF2980 Risk Management | 51833 | 7.5 credits | 7.5 |
Track, Optimization and Systems Theory (OPST)
Courses (OPST)
Mandatory courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF280X Degree Project in Optimization and Systems Theory, Second Cycle | 61558 | 30.0 credits | 15.0 | 15.0 |
At least 30 cr of the conditionally elective courses need to be studied in the field optimization and systems theory.
Conditionally elective courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| SF2852 Optimal Control Theory | 51220 | 7.5 credits | 7.5 | |||
| SF2866 Applied Systems Engineering | 50555 | 7.5 credits | 7.5 | |||
| SF2832 Mathematical Systems Theory | 51194 | 7.5 credits | 7.5 | |||
| SF2863 Systems Engineering | 50594 | 7.5 credits | 7.5 | |||
| SF2812 Applied Linear Optimization | 60860 | 7.5 credits | 7.5 | |||
| SF2842 Geometric Control Theory | 60934 | 7.5 credits | 7.5 | |||
| SF2822 Applied Nonlinear Optimization | 60873 | 7.5 credits | 7.5 |