Compulsory module (3 ECTS)
Fundamentals of Data Science (3 ECTS)
Content:
- Introduction to data science
- Infrastructure for data scientists
- Basics of data analysis
- Simple text analysis
- Communicating results
- Critical aspects of data analysis
Required elective modules (9 ECTS)
Programming
- Python for Data Science (6 ECTS)
- R Bootcamp (3 ECTS)
Basic methods
- Linear Algebra 1 (3 ECTS)
- Data Quality (3 ECTS)
Domain experience
- Customer Data Analytics (3 ECTS)
- Data Analytics for Energy Systems and IoT (3 ECTS)
- Fraud Detection (3 ECTS)
- Geospatial Data Analysis for Smart Communities (3 ECTS)
- Open (Government) Data with Tableau (3 ECTS)
- Sport Data Analytics (3 ECTS)
- Time Series Analysis in Finance (3 ECTS)
- Sustainability Analytics (3 ECTS)
- Natural Experiments Using R (requires R Bootcamp) (3 ECTS)
Human centered topics
- Ethical Issues of Big Data (3 ECTS)
- Legal Issues of Big Data (3 ECTS)
- Human Centered Design (3 ECTS)
- Data Visualisation and Narration (3 ECTS)
- Hands-on Visualisation for Data Science (3 ECTS)
- GenAI (requires Python for Data Science) (3 ECTS)
On request
- Machine Learning I (3 ECTS)
Click or tap here to consult the module descriptions for the required elective modules.
General information
The modules are taught in English and delivered on Thursdays or Fridays in each semester. You may attend them concurrently or consecutively to your master's programme.
After completing the master’s programme the Minor in Data Science and AI, you will earn an additional confirmation incl. grades for your advanced skills in Data Science.
