- Learning basic libraries such as Numpy, Pandas, Scikit-learn, Matplotlib
- Learning and applying basic Data Science, Statistics and Machine Leanring concepts
- Working with Data types
- Prepare students for advanced courses (e.g., deep learning)
- 2 weeks of full-time course and one presentation day. First week with lectures and small exercises, second week working on final assignment.
- Course content: Python libraries for data analysis: numpy, pandas, scikit-learn, statsmodels, matplotlib, seaborn, applied health data analysis
- Weekly Hours: 1st week: 3h lectures in the morning, 3h coding exercises in the afternoon, second week practical health data analysis in a team.
- Second week: Working on assignment and result presentation with Q&A (graded)
- Credits: 3
- Graded: yes
- Date: Monday 15.03.2021 - Friday, 26.03.2021
- Teaching Form: Digital Hands-on seminar
- Course Language: English
- Location: Online (Zoom)
- Participant limit: 35 participants