Content¶
This set of workshops is intended as an introduction to the Python programming language. It follows on from my introduction to R course and adopts the same philosophy of analysing data in an open and reproducible way. The final workshop in this series introduces Docker as a way to containerise your analysis. This allows you to fully capture your computational environment alongside your data and analysis scripts to ensure your work is fully reproducible.
If you spot any errors with any of the content (e.g., typos) please raise an issue by clicking on the icon in the top right 
where you can also view the source this book. You can download the content of each of the workshops in either .md or .pdf format by clicking on the download icon 
in the top right.
To view the license on how to (re)use this material click here. tldr; it’s the very simple and permissive MIT license.