Statistical learning seminar

Sarah Kaspar   2023-10-20   Comments Off on Statistical learning seminar

Date(s) - 2023-10-20 - 2023-11-17
14:00 CEST - 15:30 CET


The seminar will take place on 5 Fridays:

  • Friday, 20 Oct, 14:00 – 15:00 CET
  • Friday, 27 Oct, 14:00 – 15:30 CET
  • Friday, 03 Nov, 14:00 – 15:30 CET
  • Friday, 10 Nov, 14:00 – 15:30 CET
  • Friday, 17 Nov, 14:00 – 15:30 CET


Would you like to deepen your understanding of data analysis and machine learning? Are you interested in applications in R or Python? Then this book and coding seminar is the right activity for you.

In 5 sessions, we’ll discuss some of the the highlights of the popular book and lecture series Introduction to Statistical Learning , which covers:

  • regression and classification
  • model assessment and validation
  • trees and random forests
  • deep learning
  • survival analysis
  • principal component analysis
  • clustering

Our materials

"Introduction to statistical learning" offers publicly available learning materials in the form of

which are a great resource for self-learning. The only thing the book can’t give you are external motivation and discussions with a group of peers 🙂


Each week, we will cover one method from the book and its usage in R or Python (depending on the presenter). We won’t be able to cover the whole book in 5 days, so we’ll vote on the most interesting topics.
Before each session, you can watch the respective video lectures or read the chapter on your own pace, and we meet for code demo and discussion. We roughly plan

  • 30 min for reviewing the method
  • 30 min for a demo in R or Python
  • 30 min time for further discussions

If you join this seminar, please consider contributing. You may

  • review a method (i.e. the content of a chapter or subchapter), or
  • prepare a demonstration in R or python (you choose!) following the online scripts.

These presentations don’t have to be exhaustive – after all, the in-depth explanations are available as online lectures and book chapters.

Contributions remain voluntary, to also allow those that don’t feel confident with presenting to join. However, we need a few presenters to make it happen.

Who is this seminar for

Anyone is welcome to join the book seminar, but it’s not a beginner’s course on statistics. Some basic understanding of statistics and linear models will be useful to get the best out of it.


It will be possible to attend the seminar, both in person (seminar room B18, EMBL Heidelberg) and via Zoom.


  • Sarah Kaspar, Centre for Statistical Data Analysis, EMBL Heidelberg, Germany.


We have limited space in the seminar, so please make sure that you can join at least 3 out of the 5 instances.


This event is fully booked.