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Module Leads

Derrick Bennett Derrick Bennett

Photo of Aiden Doherty Aiden Doherty

Imen Hammami

 

Learning Objectives

By the end of this module students will gain experience of:

  • How to explore the large datasets.
  • How to prepare and clean large datasets for analysis (e.g. reformatting and pre-processing).
  • How to wrangle data to obtain key exposures and outcomes
  • How to visualise and present raw, intermediate and final datasets for effective communication of the final results.
  • How to investigate different types of data using a machine learning framework
  • How to develop code and analyses using reproducible methods. 

Sessions

  1. Overview of data science and AI/ML methods
  2. Processing phenotype data
  3. Data visualisation using R
  4. Reproducible research
  5. Introduction to unsupervised machine learning
  6. Processing a complex exposure