The course covered content for these learning objectives:

To write your own custom functions
To use for loops, apply functions and if statements
To analyse large matrices of data in a semi-automated way
To normalise data
To quantify and correct batch effect
To undertake the most common clustering algorithms including k-means and hierarchical
To perform variable selection and present these results in different plots including heatmaps
To do 2-way ANOVA
To undertake multivariate modelling
A brief introduction to machine learning.

The course included brief theoretical introductions followed by hands on exercises based on real life research examples.