Learning goals: technical perspective
- Fundamentals of programming (with a focus on data analysis and machine learning)
- Data handling
Learning goals: analytical perspective
- Preparation of data using popular open-source-programming environments (such as Python)
- Statistical modelling, machine learning, artificial intelligence
- Practical applications
Learning goals: decision maker’s perspective
- Students that have acquired the DSF-Certificate:
- Identify the potential of creating business and societal value out of data
- Can communicate and work with “technical” and legal experts in a proactive and solution-oriented manner
- Can explain the strengths or weaknesses of proposed solutions to those members of the management less well versed in technical matters
- In general have a sound ability to reflect on the methods and phenomena of the digital age
Extensive focus on data science, machine learning and programming
- Fundamentals of programming.
- Data handling.
- Statistical modelling.
- Classification.
- Regression.
- Neural networks.
- Forecasting.
Multidisciplinary perspectives on data science
- Data-driven business strategies.
- Ethical aspects.
- Legal aspects.
- Political aspects.
- Micro- and macroeconomic aspects.
For the elective courses of the DSF programme, you can choose from the courses listed here.
Most courses offered in the Spring Term or Fall Term will be offered in future again; but we cannot guarantee the course implementation in future. New courses will be added on a rolling basis.
Participants starting the DSF program in Fall can choose courses offered in the same semester and later at their BA-level.
Both compulsary courses and the vast majority of the elective courses are taught in English