Curriculum for Business Analytics
Programme provision
To obtain the MSc degree in Business Analytics the student must fulfil the following requirements:
- Have passed Polytechnical foundation courses adding up to at least 10 ECTS
- Have passed Programme-specific courses adding up to at least 50 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 (10 ECTS)
The following courses are mandatory:
| 12100 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | F7 (Tues 18-22) |
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| 12106 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | Autumn E3B (Fri 13-17) |
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| 12105 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | E7 (Tues 18-22) |
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| 12101 | Quantitative methods to assess sustainability (Polytechnical Foundation) | 5 | point | Spring F3B (Fri 13-17) |
| 42504 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | August |
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| 42501 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | June |
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| 42500 | Innovation in Engineering (Polytechnical Foundation) | 5 | point | January |
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 |
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| 42505 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | August |
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| 42503 | Facilitating Innovation in Multidisciplinary Teams | 5 | point | June |
Programme specific courses (50 ECTS)
Innovation II course - mandatory (5 ECTS):
| 42576 | From Analytics to Action | 5 | point | Spring F1A (Mon 8-12) |
Core competence courses - mandatory (15 ECTS)
| 42114 | Integer Programming | 5 | point | Autumn E4A (Tues 13-17) |
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| 42137 | Optimization using metaheuristics | 5 | point | Spring F2A (Mon 13-17) |
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| 42112 | Mathematical Programming Modelling | 5 | point | January |
| 42577 | Introduction to Business Analytics | 5 | point | Autumn E1A (Mon 8-12) |
| 42578 | Advanced Business Analytics | 5 | point | Spring F3B (Fri 13-17) |
Core competence introductory courses - choose at most 20 ECTS among the following courses:
| 02270 | Cybersecurity Fundamentals | 5 | point | Autumn E5B (Wed 13-17) |
| 02417 | Time Series Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 02443 | Stochastic Simulation | 5 | point | June |
| 02805 | Social graphs and interactions | 10 | point | Autumn E5 (Wed 8-17) |
| 02806 | Social data analysis and visualization | 5 | point | Spring F3A (Tues 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) |
| 42137 | Optimization using metaheuristics | 5 | point | Spring F2A (Mon 13-17) |
| 42180 | Quantitative modelling of behaviour | 5 | point | Spring F3A (Tues 8-12) |
| 42189 | Transport System Analysis | 5 | point | Spring F4B (Fri 8-12) |
| 42380 | Supply Chain Analytics | 5 | point | Spring F5A (Wed 8-12) |
| 42417 | Simulation in Operations Management | 5 | point | June |
Core competence advanced courses - choose at least 10 ECTS among the following courses:
| 02427 | Advanced Time Series Analysis | 10 | point | Autumn E5 (Wed 8-17) |
| 02435 | Decision-Making Under Uncertainty | 5 | point | Spring F4A (Tues 13-17) |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
| 02460 | Advanced Machine Learning | 5 | point | Spring F1B (Thurs 13-17) |
| 02517 | Responsible AI: Algorithmic fairness and explainability | 5 | point | Autumn E2B (Thurs 8-12) |
| 02582 | Computational Data Analysis | 5 | point | Spring F2B (Thurs 8-12) |
| 42136 | Large Scale Optimization using Decomposition | 5 | point | Spring F2B (Thurs 8-12) |
| 42186 | Model-based machine learning | 5 | point | Spring F5B (Wed 13-17) |
| 42879 | Decision Support and Strategic Assessment | 5 | point | Autumn E2B (Thurs 8-12) |
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
Dario Pacino Associate Professor Phone: +45 45251512 darpa@dtu.dk