This lesson starts with a discussion of working with data in Julia, how to use the DataFrames.jl package and how to visualise data. It then moves on to linear algebra approaches, followed by classical machine learning approaches as well as deep learning methods with an example of scientific ML. Finally, key aspects of regression, time series prediction and analysis is covered.