Courses for Applied and Computational Mathematics

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

• Advanced Computation in Fluid Mechanics (DD2365) 7.5 credits
• Numerical Solutions of Differential Equations (SF2521) 7.5 credits
• Computational Methods for Stochastic Differential Equations and Machine Learning (SF2525) 7.5 credits
• Numerical algorithms for data-intensive science (SF2526) 7.5 credits
• Project Course in Scientific Computing (SF2567) 7.5 credits

At least 30 cr need to be studied on the track: 15 cr compulsory courses + 15 cr of the conditionally elective courses.

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.

Mandatory courses

• Financial Mathematics, Basic Course (SF2701) 7.5 credits

Conditionally elective courses

• Regression Analysis (SF2930) 7.5 credits
• Time Series Analysis (SF2943) 7.5 credits
• Martingales and Stochastic Integrals (SF2971) 7.5 credits

Compulsory courses on the track (15 cr) + conditionally elective courses (15 cr) = 30 cr.

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.

Mandatory courses

• Computer Intensive Methods in Mathematical Statistics (SF2955) 7.5 credits

Conditionally elective courses

• Algorithms and Complexity (DD2352) 7.5 credits
• Computational Methods for Stochastic Differential Equations and Machine Learning (SF2525) 7.5 credits
• Numerical algorithms for data-intensive science (SF2526) 7.5 credits
• Parallel Computations for Large- Scale Problems (SF2568) 7.5 credits
• Regression Analysis (SF2930) 7.5 credits
• Time Series Analysis (SF2943) 7.5 credits

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

• Applied Linear Optimization (SF2812) 7.5 credits
• Applied Nonlinear Optimization (SF2822) 7.5 credits
• Mathematical Systems Theory (SF2832) 7.5 credits
• Geometric Control Theory (SF2842) 7.5 credits
• Systems Engineering (SF2863) 7.5 credits
• Applied Systems Engineering (SF2866) 7.5 credits

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.

Mandatory courses

• Degree Project in Scientific Computing, Second Cycle (SF250X) 30.0 credits
• Matrix Computations for Large-scale Systems (SF2524) 7.5 credits

Conditionally elective courses

• The Finite Element Method (SF2561) 7.5 credits
• Program Construction in C++ for Scientific Computing (SF2565) 7.5 credits
• Project Course in Scientific Computing (SF2567) 7.5 credits

At least 30 cr need to be studied on the track: 15 cr compulsory courses + 15 cr of the conditionally elective courses.

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.

Mandatory courses

• Degree Project in Financial Mathematics, Second Cycle (SF291X) 30.0 credits
• Portfolio Theory and Risk Management (SF2942) 7.5 credits

Conditionally elective courses

• Financial Derivatives (SF2975) 7.5 credits
• Risk Management (SF2980) 7.5 credits

Compulsory courses on the track (15 cr) + conditionally elective courses (15 cr) = 30 cr.

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.

Mandatory courses

• Degree Project in Mathematical Statistics, Second Cycle (SF290X) 30.0 credits
• Modern Methods of Statistical Learning (SF2935) 7.5 credits

Conditionally elective courses

• Topological Data Analysis (SF2956) 7.5 credits
• Statistical Machine Learning (SF2957) 7.5 credits

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.

Mandatory courses

• Degree Project in Optimization and Systems Theory, Second Cycle (SF280X) 30.0 credits

Conditionally elective courses

• Mathematical Systems Theory (SF2832) 7.5 credits
• Optimal Control Theory (SF2852) 7.5 credits
• Systems Engineering (SF2863) 7.5 credits
• Applied Systems Engineering (SF2866) 7.5 credits