Having some foundational understanding of how to code in R, this module will provide initially an overview of the different types of Machine Learning, and then will provide some practical, hands-on examples of creating ML models.

Time estimation: 3 hours

Learning objectives:

• Understand the ML taxonomy and the commonly used machine learning algorithms for analysing -omics data
• Understand differences between ML algorithms categories and to which kind of problem they can be applied
• Understand different applications of ML in different -omics studies
• Use some basic, widely used R packages for ML
• Interpret and visualize the results obtained from ML analyses on omics datasets
• Apply the ML techniques to analyse their own datasets