Here is the best PCA explanation I ever read on the web: https://stats.stackexchange.com/questions/2691/making-sense-...
https://www.mathworks.com/help/stats/biplot.html
The use of car data and how it correlates is a good way of showing how PCA treats each variable. For example acceleration and weight are negatively correlated while displacement and horsepower are highly correlated.
I used Octave in Andrew Ng’s ML class and wanted to learn more Matlab so I signed up for a Coursera course on it.
It’s a nice tool.
Matlab is very popular in engineering. It’s simple enough to get simple things done without needing to know too much CS.