Curriculum for Business Analytics

Programme provision

In order 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 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

42504 Innovation in Engineering (Polytechnical Foundation) 5 point August
or
42501 Innovation in Engineering (Polytechnical Foundation) 5 point June
or
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
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 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)
or
42137 Optimization using metaheuristics 5 point Spring F2A (Mon 13-17)
or
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 25 ECTS among the following courses:

02239 Data Security 7.5 point Autumn E5B (Wed 13-17)
02417 Time Series Analysis 5 point Spring F4B (Fri 8-12)
02431 Risk Management 5 point January
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)
42178 Transport system analysis - demand and planning 5 point Autumn E5B (Wed 13-17)
42180 Quantitative modelling of behaviour 5 point Spring F3A (Tues 8-12)
42380 Supply Chain Analytics 5 point Spring F5A (Wed 8-12)
42417 Simulation in Operations Management 5 point June
63851 Project Management 5 point August and January

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)
02443 Stochastic Simulation 5 point June
02456 Deep learning 5 point Autumn E2A (Mon 13-17)
02460 Advanced Machine Learning 5 point Spring F1B (Thurs 13-17)
02582 Computational Data Analysis 5 point Spring F2B (Thurs 8-12)
42117 Transport Optimization 5 point Autumn E2B (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