Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI

Python for Data Science in Digital Health (Wintersemester 2021/2022)

Dozent: Prof. Dr. Christoph Lippert (Digital Health - Machine Learning)
Tutoren: M.Sc. Aiham Taleb Jana Fehr

Allgemeine Information

  • Semesterwochenstunden: 2
  • ECTS: 3
  • Benotet: Ja
  • Einschreibefrist: 01.10.2021 - 22.10.2021
  • Lehrform: compact course V / Übung
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch
  • Maximale Teilnehmerzahl: 35

Studiengänge, Modulgruppen & Module

Digital Health MA


General Information

  • Basic introduction into Datascience using Python
  • 2 weeks of full-time course and one presentation day.
  • First week with lectures in the morning and hands-on exercises in the afternoon
  • Second week comprises working on final assignment in groups and presenting results on the last course day (Friday)
  • 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.
  • Credits: 3
  • Graded: yes
  • Date: Monday March 28th-April 8th
  • Teaching Form: Digital Hands-on seminar
  • Course Language: English
  • Location: TBD (Depends on the Covid-situation, was fully online in 2021)
  • Participant limit: 35 participants


  • 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)

Course Structure

  • First week
    • Morning lecture
    • Afternoon hands-on exercises and discussing solutions
    • Handout of project assignment
  • Second week
    • Working on assignment
    • Friday: Presenting final project assignment for week 2

If you have further questions, please contact teaching-lippert@hpi.de


Google Colab or Jupyter Notebook environment:

We will work with notebooks in google colab to ensure consistent programming environments for everyone. If you don't want to use google colab, you can set up your notebook in jupyter i.e. with Anaconda. Here you can find a link on how to do this. Please be ready to open notebooks with either colab or jupyter when the course starts.


Basic programming skills

We will assume that participants have programmed before, i.e. know how to

  • write and call functions
  • work with external libraries
  • use different data-types (int, char, strings, list, dictionaries)
  • write loops, ...

in at least one programming language. If you want to look up how to do this in python, we recommend checking out this tutorial.

Or enroll in the self-paced open HPI course ‘Fundamentals of Programming for Digital Health
https://open.hpi.de/courses/hpi-dh-fprog2021. This course also provides auto-graded exercises.


  • Solving a data analysis assignment in a team of max. 5 people
  • 30min Team presentation on analysis results (70% team grade)
  • 15min Q&A after presentation (30% individual grade) 


Monday March 28th, 2022 until Friday April 8th, 2022