Building Machine Learning Pipelines in Python with Scikit-learn

Free Live ML Workshop #6 on Dec 3 - Register Now

dotsdots

Foundations of Sports Analytics: Data, Representation, and Models in Sports

Description

This course provides an introduction to using Python to analyze team performance in sports. Learners will discover a variety of techniques that can be used to represent sports data and how to extract narratives based on these analytical techniques. The main focus of the introduction will be on the use of regression analysis to analyze team and player performance data, using examples drawn from the National Football League (NFL), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier LEague (EPL, soccer) and the Indian Premier League (IPL, cricket).Read more.

This resource is offered by an affiliate partner. If you pay for training, we may earn a commission to support this site.

Career Relevance by Data Role

The techniques and tools covered in Foundations of Sports Analytics: Data, Representation, and Models in Sports are most similar to the requirements found in Business Analyst job advertisements.

Similarity Scores (Out of 100)

Learning Sequence

Foundations of Sports Analytics: Data, Representation, and Models in Sports is a part of one structured learning path.

Coursera
University of Michigan

5 Courses 7 Months

Sports Performance Analytics