This repository contains some (text heavy) training slides I produced for colleagues, in the form of a Jupyter notebook that has been converted to an HTML slideshow. Clone the repository and open the .html file in your browser.
It is aimed at GIS users with a non-computer science background, who find themselves having to write code to manipulate large raster datasets (in the form of large arrays) to perform analysis that is outside the scope of commercial or other GIS packages.
The large data sizes involved often mean that some level of understanding of some of the fundamentals of how computers work is beneficial. These notes aim to give a basic grounding in this, and use this understanding to explain and demonstrate why some forms of a simple array-processing algorithm are so much faster than others.
Note that follow-up sessions covered more hands-on material that was specific to work within the Malaria Atlas Project and are thus not provided in this github copy of the repo.