Curriculum for Mathematical Modelling and Computation
Programme provision
In order to obtain the MSc degree in Mathematical Modelling and Computation the student must fulfill the following requirements:
- Have passed Polytechnical foundation courses adding up to at least 5 ECTS
- Have passed Programme specific courses adding up to at least 55 ECTS
- Have performed a Master thesis of 30 ECTS points within the field of the general program
- Have passed a sufficient number of Elective courses to bring the total number of ECTS of the entire study to 120 ECTS
Curriculum
Polytechnical foundation courses (5 ECTS)
The following course is mandatory
| 42500 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | January |
| or | ||||
| 42504 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | August |
| or | ||||
| 42501 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | June |
Students with advanced innovation competences may take one of the following courses as an alternative to 42500/42501/42504:
| 42502 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | January |
| or | ||||
| 42505 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | August |
| or | ||||
| 42503 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | June |
Programme specific courses (55 ECTS)
Innovation course II - choose 5 ECTS among the following courses - if more than 5 ECTS are chosen they will count as electives:
| 02492 | Digital Learning Technology and Entrepreneurship | 5 | point | Autumn E3A (Tues 8-12) |
| 02809 | UX Design Prototyping | 5 | point | Autumn E1A (Mon 8-12) |
| 38102 | Technology Entrepreneurship | 5 | point | Autumn E1B (Thurs 13-17) |
| 38103 | X-Tech Entrepreneurship | 10 | point | Spring F3 (Tues 8-12, Fri 13-17), Autumn E3 (Tues 8-12, Fri 13-17) |
| 38106 | Developing an Entrepreneurial mindset through serious game | 5 | point | Spring F1B (Thurs 13-17), Autumn E1B (Thurs 13-17) |
| 42576 | From Analytics to Action | 5 | point | Spring F1A (Mon 8-12) |
Core competence courses - mandatory (10 ECTS)
| 01617 | Introduction to Dynamical Systems | 5 | point | Autumn E3B (Fri 13-17) |
| 02613 | Python and High-Performance Computing | 5 | point | Spring F5A (Wed 8-12) |
Core competence courses - choose 5 ECTS from each of the following two groups of courses:
Optimization
| 02612 | Constrained Optimization | 5 | point | Spring F4A (Tues 13-17) |
| 42114 | Integer Programming | 5 | point | Autumn E4A (Tues 13-17) |
Please note that 42114 Integer Programming is a mandatory prerequisite for some of the more advanced courses on operations research.
Statistics
| 02409 | Multivariate Statistics | 5 | point | Autumn E1A (Mon 8-12) |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
Choose 30 ECTS among the rest of the programme specific courses:
| 01238 | Differential Geometry | 5 | point | Spring F2B (Thurs 8-12) |
| 01257 | Advanced Modelling - Applied Mathematics | 5 | point | January |
| 01325 | Function spaces and mathematical analysis | 5 | point | Spring F5B (Wed 13-17) |
| 01405 | Algebraic Error-Correcting Codes | 5 | point | Spring F4B (Fri 8-12) |
| 01415 | Computational Discrete Mathematics | 5 | point | Autumn E5B (Wed 13-17) |
| 01426 | Cryptology 2 | 5 | point | Autumn E3A (Tues 8-12) |
| 01617 | Introduction to Dynamical Systems | 5 | point | Autumn E3B (Fri 13-17) |
| 01621 | Advanced Dynamical Systems: Global Theory | 5 | point | Spring F1A (Mon 8-12) |
| 01622 | Advanced Dynamical Systems: Applications in Science and Engineering | 5 | point | Spring F3B (Fri 13-17) |
| 01715 | Functional Analysis | 5 | point | Autumn E4B (Fri 8-12) |
| 02232 | Applied Cryptography | 5 | point | Autumn E1B (Thurs 13-17) |
| 02246 | Model Checking | 7.5 | point | Autumn E4A (Tues 13-17) |
| 02249 | Computationally Hard Problems | 7.5 | point | Autumn E3A (Tues 8-12) |
| 02255 | Modern Cryptology | 5 | point | Spring F5B (Wed 13-17) |
| 02407 | Stochastic Processes - Probability 2 | 5 | point | Autumn E3A (Tues 8-12) |
| 02409 | Multivariate Statistics | 5 | point | Autumn E1A (Mon 8-12) |
| 02411 | Statistical Design and Analysis of Experiments | 5 | point | Autumn E2A (Mon 13-17), Spring F1A (Mon 8-12) |
| 02417 | Time Series Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 02421 | Stochastic Adaptive Control | 5 | point | Spring F3A (Tues 8-12) |
| 02424 | Advanced Dataanalysis and Statistical Modelling | 5 | point | Spring F2A (Mon 13-17) |
| 02427 | Advanced Time Series Analysis | 10 | point | Autumn E5 (Wed 8-17) |
| 02429 | Analysis of correlated data: Mixed linear models | 5 | point | Autumn E2B (Thurs 8-12) |
| 02431 | Risk Management | 5 | point | January |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 02458 | Cognitive Modelling | 5 | point | Autumn E2B (Thurs 8-12) |
| 02460 | Advanced Machine Learning | 5 | point | Spring F1B (Thurs 13-17) |
| 02471 | Machine learning for signal processing | 5 | point | Autumn E1B (Thurs 13-17) |
| 02477 | Bayesian machine learning | 5 | point | Spring F2A (Mon 13-17) |
| 02492 | Digital Learning Technology and Entrepreneurship | 5 | point | Autumn E3A (Tues 8-12) |
| 02501 | Advanced Deep Learning in Computer Vision | 5 | point | Spring F4A (Tues 13-17) |
| 02506 | Advanced Image Analysis | 5 | point | Spring F5B (Wed 13-17) |
| 02516 | Introduction to Deep Learning in Computer Vision | 5 | point | January |
| 02561 | Computer Graphics | 5 | point | Autumn E5A (Wed 8-12) |
| 02562 | Rendering - Introduction | 5 | point | Autumn E5B (Wed 13-17) |
| 02563 | Generative Methods for Computer Graphics | 5 | point | Spring F1B (Thurs 13-17) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 02612 | Constrained Optimization | 5 | point | Spring F4A (Tues 13-17) |
| 02614 | High-Performance Computing | 5 | point | January |
| 02616 | Large-scale Modelling | 5 | point | Spring F3A (Tues 8-12) |
| 02619 | Model Predictive Control | 5 | point | Autumn E2B (Thurs 8-12) |
| 02623 | The Finite Element Method for Partial Differential Equations | 5 | point | January |
| 02624 | Inverse problems and Imaging | 5 | point | Autumn E5B (Wed 13-17) |
| 02686 | Scientific computing for differential equations | 5 | point | Spring F1B (Thurs 13-17) |
| 02687 | Scientific Computing for ordinary and partial differential equations | 5 | point | Spring F1A (Mon 8-12) |
| 02807 | Computational Tools for Data Science | 5 | point | E7 (Tues 18-22) |
| 42112 | Mathematical Programming Modelling | 5 | point | January |
| 42114 | Integer Programming | 5 | point | Autumn E4A (Tues 13-17) |
| 42115 | Network Optimization | 5 | point | Autumn E4B (Fri 8-12) |
| 42136 | Large Scale Optimization using Decomposition | 5 | point | Spring F2B (Thurs 8-12) |
| 42137 | Optimization using metaheuristics | 5 | point | Spring F2A (Mon 13-17) |
| 42186 | Model-based machine learning | 5 | point | Spring F5B (Wed 13-17) |
Elective Courses
Any course classified as MSc course in DTU's course base may be an elective course. This includes programme specific courses in excess of the minimal requirements. Master students may choose as much as 10 credit points among the bachelor courses at DTU and courses at an equivalent level from other higher institutions. In addition, it is possible to take MSc-level courses at other Danish universities or abroad.
Head of studies
Yiqiu Dong Associate Professor Phone: +45 45253108 yido@dtu.dk