Appendix 1: Course list

Master's Programme, Applied and Computational Mathematics, 120 credits (TTMAM), Programme syllabus for studies starting in autumn 2019

General courses

Year 1

Mandatory courses (22.5 credits)

Course code Course name Credits Edu. level
AK2040 Theory and Methodology of Science with Applications Computational Science) 7.5 Second cycle
SF2520 Applied Numerical Methods 7.5 Second cycle
SF2940 Probability Theory 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
SF2812 Applied Linear Optimization 7.5 Second cycle
SF2832 Mathematical Systems Theory 7.5 Second cycle
SF2863 Systems Engineering 7.5 Second cycle

Recommended courses

Course code Course name Credits Edu. level
DD2257 Visualization 7.5 Second cycle
DD2356 Methods in High Performance Computing 7.5 Second cycle
DD2365 Advanced Computation in Fluid Mechanics 7.5 Second cycle
DD2421 Machine Learning 7.5 Second cycle
DD2434 Machine Learning, Advanced Course 7.5 Second cycle
DD2435 Mathematical Modelling of Biological Systems 9.0 Second cycle
SF1811 Optimization 6.0 First cycle
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 7.5 Second cycle
SF2526 Numerical algorithms for data-intensive science 7.5 Second cycle
SF2565 Program Construction in C++ for Scientific Computing 7.5 Second cycle
SG2212 Computational Fluid Dynamics 7.5 Second cycle
SG2224 Applied Computational Fluid Dynamics 5.0 Second cycle

Supplementary information

At least one of the conditionally elective courses has to be studied. The course/courses can be studies either during year one or two.

Note that due to overlap it is not possible to select both SF2935 and DD2421.

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

Year 2

Conditionally elective courses

Course code Course name Credits Edu. level
SF2832 Mathematical Systems Theory 7.5 Second cycle
SF2863 Systems Engineering 7.5 Second cycle

Recommended courses

Course code Course name Credits Edu. level
DD2257 Visualization 7.5 Second cycle
DD2421 Machine Learning 7.5 Second cycle
DD2434 Machine Learning, Advanced Course 7.5 Second cycle
DD2435 Mathematical Modelling of Biological Systems 9.0 Second cycle
SF1811 Optimization 6.0 First cycle
SF2565 Program Construction in C++ for Scientific Computing 7.5 Second cycle

Supplementary information

At least one of the conditionally elective courses during year one and two has to be studied.

Note that due to overlap it is not possible to select both SF2935 and DD2421.

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

Year 3

Track, Computational Mathematics (COMA)

Year 1

Conditionally elective courses

Course code Course name Credits Edu. level
DD2365 Advanced Computation in Fluid Mechanics 7.5 Second cycle
SF2521 Numerical Solutions of Differential Equations 7.5 Second cycle
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 7.5 Second cycle
SF2567 Project Course in Scientific Computing 7.5 Second cycle
SF2568 Parallel Computations for Large- Scale Problems 7.5 Second cycle

Year 2

Mandatory courses (7.5 credits)

Course code Course name Credits Edu. level
SF2524 Matrix Computations for Large-scale Systems 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
SF2561 The Finite Element Method 7.5 Second cycle
SF2565 Program Construction in C++ for Scientific Computing 7.5 Second cycle
SF2567 Project Course in Scientific Computing 7.5 Second cycle

Year 3

Track, Mathematics of Data Science (DAVE)

Year 1

Mandatory courses (7.5 credits)

Course code Course name Credits Edu. level
SF2955 Computer Intensive Methods in Mathematical Statistics 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
DD2352 Algorithms and Complexity 7.5 Second cycle
SF2525 Computational Methods for Stochastic Differential Equations and Machine Learning 7.5 Second cycle
SF2526 Numerical algorithms for data-intensive science 7.5 Second cycle
SF2568 Parallel Computations for Large- Scale Problems 7.5 Second cycle
SF2930 Regression Analysis 7.5 Second cycle
SF2943 Time Series Analysis 7.5 Second cycle

Year 2

Mandatory courses (7.5 credits)

Course code Course name Credits Edu. level
SF2935 Modern Methods of Statistical Learning 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
SF2956 Topological Data Analysis 7.5 Second cycle
SF2957 Statistical Machine Learning 7.5 Second cycle

Track, Financial Mathematics (FMIA)

Year 1

Mandatory courses (7.5 credits)

Course code Course name Credits Edu. level
SF2701 Financial Mathematics, Basic Course 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
SF2930 Regression Analysis 7.5 Second cycle
SF2943 Time Series Analysis 7.5 Second cycle

Year 2

Mandatory courses (7.5 credits)

Course code Course name Credits Edu. level
SF2942 Portfolio Theory and Risk Management 7.5 Second cycle

Conditionally elective courses

Course code Course name Credits Edu. level
SF2975 Financial Derivatives 7.5 Second cycle
SF2980 Risk Management 7.5 Second cycle

Track, Optimization and Systems Theory (OPST)

Year 1

Conditionally elective courses

Course code Course name Credits Edu. level
SF2812 Applied Linear Optimization 7.5 Second cycle
SF2822 Applied Nonlinear Optimization 7.5 Second cycle
SF2832 Mathematical Systems Theory 7.5 Second cycle
SF2842 Geometric Control Theory 7.5 Second cycle
SF2863 Systems Engineering 7.5 Second cycle
SF2866 Applied Systems Engineering 7.5 Second cycle

Year 2

Conditionally elective courses

Course code Course name Credits Edu. level
SF2832 Mathematical Systems Theory 7.5 Second cycle
SF2852 Optimal Control Theory 7.5 Second cycle
SF2863 Systems Engineering 7.5 Second cycle
SF2866 Applied Systems Engineering 7.5 Second cycle

Year 3