Elective courses in the Master in Business Engineering - Operations Management
In the master in Business Engineering: Data Analytics you can choose elective courses for a total of 12 credits, divided over the first and the second year of the master. Most students choose to take 6 credits in the first year and another 6 credits in the second year of the programme but this is not an obligation. You can choose how you spread the elective courses, the only condition is that you took at least 12 credits in elective courses at the end of the programme.
All details about the course content, the responsible professor, medium of instruction, .... can be found in the Study Guide.
Below you can find an overview of all possibilities:
- Students can choose 12 credits from 1 or more modules listed below.
- Some courses mentioned in the list below are organised in a modular structure (these are the general courses from the master in Business Economics). These courses have been marked with the letter 'M' in the list below. Other deadlines apply for these courses
- modular courses organised in the first block of the first semester: it is not possible to enrol or make changes after October 3rd 2021
- modular courses organised in the first block of the second semester: it is not possible to enrol or make changes after February 13th 2022
- The elective course 'internship' is also bound to specific deadlines, depending on when you will be doing the internship. More information about the elective course 'internship'.
| Module: Elective Advanced Courses | ||
| course | credits | semester |
| Analytical Customer Relationship Management | 6 | 1 |
| Machine Learning | 6 | 1 |
| Predictive and Prescriptive Analytics | 6 | 2 |
| Big Data | 6 | 1 |
| Investment Analysis | 6 | 1 |
| Business Valuation | 4 | 1 |
| Management Accounting | 4 | 1 |
| Financial Risk Management | 6 | 1 |
| Econometrics: Time Series Analysis | 6 | 1 |
| Networks in Socio-economic Systems | 6 | 2 |
| Deep Learning | 6 | 2 |
| Internship | 6 | J |
| Artificial Intelligence | 6 | 1 |
| Clean Technology | 5 | 1 |
| Rational Use of Materials | 5 | 1 |
| Heuristics and Search Methods | 4 | 1 |
| Methods Engineering and work Measurement | 6 | 1 |
| Advanced Databases | 6 | 1 |
| Information Technology and Data Processing | 6 | 2 |
| Network Modelling and Design | 4 | 2 |
| Quality Engineering and Industrial Statistics | 6 | 1 |
| Queueing Theory | 6 | 2 |
| Software Architecture | 4 | 1 |
| Total Plant Automation | 6 | 2 |
| Module: Elective General Courses |
||
| course | credits | semester |
| Economics of Banking | 6 | 1 |
| Economics of Financial Markets | 6 | 1 |
| Advanced Econometrics: Non-linear Methods | 6 | 2 |
| Advanced Microeconomics: Game Theory and Asymmetric Information | 6 | 1 |
| Microeconomics: Decision Theory | 6 | 1 |
| Monetary Economics | 5 | 1 |
| Ecological Economics | 6 | 2 |
| Insurances | 6 | 1 |
| Audit (M) | 6 | 1 |
| Management Control (M) | 6 | 2 |
| Taxation | 5 | 2 |
| Advanced Financial Statement Analysis (M) | 6 | 1 |
| Market Research Methods (M) | 6 | 1 |
| Corporate Social Responsibility | 3 | 2 |
| Law and Economics | 3 | 2 |
| Environmental Economics | 4 | 1 |
| Ethics, Engineering and Society | 3 | 2 |
| Health Economics | 5 | 1 |
| Coaching and Diversity | 3 | J |
| Movement and Sports: Now and Later | 3 | 2 |
| Sustainability Thinking | 5 | J |
| Module: Elective Courses Academic Teacher Education |
||
| course | credits | semester |
| Powerful Learning Environments | 6 | 1 |
| Classroom Management and Reflection | 4 | 2 |
| The Teacher within School and Society | 4 | 1 |
| Psychology of Adolescence | 4 | 1 |