The following courses are part of study year one.

The course application codes and study periods are valid for the academic year 2021/2022. For other academic years, different application codes and study periods may apply.

General courses

At least one of the conditionally elective courses among the general courses has to be studied.

The list of recommended courses is those that we think you will need for your future career.

Mandatory courses

Course code and name Appl.code Scope P1 P2 P3 P4
AK2040 Theory and Methodology of Science with Applications (Computational Science) 50074 7.5 hp 7.5
SF2940 Probability Theory 50206 7.5 hp 7.5
SF2520 Applied Numerical Methods 50389 7.5 hp 3.0 4.5

Conditionally elective courses

Course code and name Appl.code Scope P1 P2 P3 P4
SF2832 Mathematical Systems Theory 50171 7.5 hp 7.5
SF2863 Systems Engineering 50411 7.5 hp 7.5
SF2812 Applied Linear Optimization 60154 7.5 hp 7.5

Recommended courses

Course code and name Appl.code Scope P1 P2 P3 P4
DD2257 Visualization 50478 7.5 hp 7.5
DD2435 Mathematical Modelling of Biological Systems 50494 9.0 hp 6.0 3.0
SF2565 Program Construction in C++ for Scientific Computing 50486 7.5 hp 3.5 4.0
DD2434 Machine Learning, Advanced Course 50172 7.5 hp 7.5
SF1811 Optimization 50106 6.0 hp 6.0
DD2421 Machine Learning 60128 7.5 hp 7.5
SF2526 Numerical algorithms for data-intensive science 60346 7.5 hp 7.5
SG2212 Computational Fluid Dynamics 60310 7.5 hp 7.5
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 60345 7.5 hp 4.0 3.5
DD2356 Methods in High Performance Computing 60394 7.5 hp 7.5
DD2365 Advanced Computation in Fluid Mechanics 60402 7.5 hp 7.5
SG2224 Applied Computational Fluid Dynamics 60367 5.0 hp 5.0

Optional courses

Course code and name Appl.code Scope P1 P2 P3 P4
SF2561 The Finite Element Method 50480 7.5 hp 7.5
SF2852 Optimal Control Theory 50214 7.5 hp 7.5
SF2866 Applied Systems Engineering 50428 7.5 hp 7.5
SF2935 Modern Methods of Statistical Learning 50348 7.5 hp 7.5
SF2942 Portfolio Theory and Risk Management 50488 7.5 hp 7.5
SF2956 Topological Data Analysis 50489 7.5 hp 7.5
SF2975 Financial Derivatives 50558 7.5 hp 7.5
SF2567 Project Course in Scientific Computing 50484 7.5 hp 3.7 3.8
SF2524 Matrix Computations for Large-scale Systems 50477 7.5 hp 7.5
SF2980 Risk Management 50481 7.5 hp 7.5
SF2842 Geometric Control Theory 60131 7.5 hp 7.5
SF2930 Regression Analysis 60283 7.5 hp 7.5
SF2971 Martingales and Stochastic Integrals 60386 7.5 hp 7.5
SF2521 Numerical Solutions of Differential Equations 60274 7.5 hp 3.7 3.8
SF2701 Financial Mathematics, Basic Course 60289 7.5 hp 7.5
SF2822 Applied Nonlinear Optimization 60133 7.5 hp 7.5
SF2943 Time Series Analysis 60155 7.5 hp 7.5
SF2955 Computer Intensive Methods in Mathematical Statistics 60379 7.5 hp 7.5
SF2568 Parallel Computations for Large- Scale Problems 7.5 hp

Specialisations

Track, Computational Mathematics (COMA)

Courses (COMA)

At least 3 conditionally elective courses on the track have to be studied during year 1 and 2. Among these 3 courses SF2521 or SF2561 needs to be studied.

Conditionally elective courses

Course code and name Appl.code Scope P1 P2 P3 P4
SF2567 Project Course in Scientific Computing 50484 7.5 hp 3.7 3.8
SF2526 Numerical algorithms for data-intensive science 60346 7.5 hp 7.5
SF2521 Numerical Solutions of Differential Equations 60274 7.5 hp 3.7 3.8
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 60345 7.5 hp 4.0 3.5
DD2365 Advanced Computation in Fluid Mechanics 60402 7.5 hp 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
SF2955 Computer Intensive Methods in Mathematical Statistics 60379 7.5 hp 7.5

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
SF2526 Numerical algorithms for data-intensive science 60346 7.5 hp 7.5
SF2930 Regression Analysis * 60283 7.5 hp 7.5
DD2352 Algorithms and Complexity 60158 7.5 hp 3.0 4.5
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 60345 7.5 hp 4.0 3.5
SF2943 Time Series Analysis * 60155 7.5 hp 7.5
SF2568 Parallel Computations for Large- Scale Problems 7.5 hp

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
SF2701 Financial Mathematics, Basic Course 60289 7.5 hp 7.5

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 you also have to study SF2971 in year 1.

Conditionally elective courses

Course code and name Appl.code Scope P1 P2 P3 P4
SF2930 Regression Analysis 60283 7.5 hp 7.5
SF2971 Martingales and Stochastic Integrals Required for SF2975 60386 7.5 hp 7.5
SF2943 Time Series Analysis 60155 7.5 hp 7.5

Track, Optimization and Systems Theory (OPST)

Courses (OPST)

At least 30 cr of the conditionally elective courses need to be studied in the field optimization and systems theory:
At least 7,5 cr of the conditionally elective courses among the general courses + at least 22,5 cr of the conditionally elective courses on the track = 30 cr.

Conditionally elective courses

Course code and name Appl.code Scope P1 P2 P3 P4
SF2866 Applied Systems Engineering 50428 7.5 hp 7.5
SF2832 Mathematical Systems Theory 50171 7.5 hp 7.5
SF2863 Systems Engineering 50411 7.5 hp 7.5
SF2812 Applied Linear Optimization 60154 7.5 hp 7.5
SF2842 Geometric Control Theory 60131 7.5 hp 7.5
SF2822 Applied Nonlinear Optimization 60133 7.5 hp 7.5