Python Course on Topological Methods in Data Analysis

October 26th - 28th, Heidelberg University

In this twelve-hour workshop the participant will be introduced to the main techniques utilized in topological data analysis and their implementation provided by the python package scikit-tda. Introductions to the Mapper algorithm and persistent homology will be complemented by respective hands-on tutorial sessions. The workshop will conclude with an exploratory project of these methods on ‘real data’, which may be provided by the participants.


The course takes place in the CIP-Pool 3/103, Mathematikon INF 205, Heidelberg. There are up to 20 seats for on-site participation, which will be distributed in advance.

Lectures and tutorials will be accessible on Zoom for online participants.

Registration Deadline: October 11th, 2020

Registration is closed


Or Download here: Schedule

Corona Regulations

Please note the following information regarding on-site participation:

  • On-site participants will need to provide personal data for contact tracking at the beginning of each day.
  • You will need to wear a mask at all times
    (CoronaVO Studienbetrieb und Kunst § 3, Absatz 1, Nummer 4 )
  • Since we will need to regularly ventilate the room, you might want to bring a sweater.

Official documents:
Conditions of Admission and Participation
Information on the Processing of Personal Data
Information Required from Persons Attending Classes

Material and Exercises

Day 1

Exercises (last updated: Oct 28th)

Day 2


Slides (Sebastian Damrich)

Day 3

Project Descriptions


You can find some example code for the exercises of the first two days here


Michael Bleher, Maximilian Schmahl, Daniel Spitz