Summer School

Becoming an Olympian in Sports Analytics

5 Sep 2022 - 9 Sep 2022

Becoming an Olympian in Sports Analytics is a practical course that brings together sports and data scientists to learn and discuss how to harness the power of data in sports.

More info & registration ⇗

Practical information:

5 Sep 2022 - 9 Sep 2022

University of Antwerp City Campus

English

Target audience: Everyone with basic knowledge of Python

Want to register?

Register until: 30 May 2022
Price: €250 (the fee includes course materials, lunches, coffee breaks, social activities and a networking dinner; it does not include travel and accommodation)

More info & registration ⇗

Georganiseerd door:

Leertraject

Learning trajectory 'AI in healthcare'

Becoming an Olympian in Sports Analytics

Technological improvements in recent years have increased the importance of data usage in sports. The abundance and variety in types of sports data open up many possibilities for the application of data science and machine learning techniques. However, to exploit the full potential of data usage in sports, it is important that data scientists, sports scientists and sports practitioners closely collaborate. In this course, we aim to bridge the gap between sports science, computer science and the sports industry and create a network of international sports analytics practitioners working in industry and academia.

This course contains theoretical classes on introductory topics, presentations from sports practitioners and experts on sports analytics as well as practical assignments. Applications are open until the 30th of May.

Want to become an Olympian in Sports Analytics? Find out more here.

Program

This course contains theoretical classes on introductory topics, presentations from sports practitioners and experts on sports analytics as well as a practical assignment. The global structure is as follows:

Day 1: Topics in sports physiology and data science. Introduction to hackathon case studies provided by industry partners.

Day 2-4: Specific topics of machine learning applied to sports and time to work on the case studies.

Day 5: Presentation and feedback of the work done during the hackathon.

Other sessions such as keynotes, a networking dinner and a sports-related social programme will be included as well. A detailed programme will be announced soon.