Analytics and AI for Sport

This module aims to introduce basic concepts, principles, methods and techniques of data analytics and AI for sport. It will develop skills and techniques for practical applications of data analytics using AI and machine learning through engagement in pattern discovery with data. The importance of pattern discovery with applications for data analytics will be explored. Data mining processes including data cleaning, preparation, and exploration algorithms will be introduced along with machine learning algorithms for clustering, classification, regression, and prediction.

1. Explain the concept of 'big data' and critically analyse data strategy and procedures in the context of a human-centred, ethical and inclusive approach to data

2. Critically evaluate the quality and potential limitations of sports data sets and identify strategies to clean and structure datasets appropriately

3. Manage data incorporating data architecture, cloud computing, databasing, and data mining

4. Apply and evaluate data mining techniques and models for knowledge discovery in sport related datasets

5. Apply machine learning algorithms and appraise the potential benefits and challenges of their use within sporting contexts