I've finished a university course in statistical machine learning that covered topics such as regression, classification, neural networks, SVM, PCA etc. The class was quite tough and rigorous (we had Bishop as a textbook) and we implemented the algorithms, but I'd like to solidify my knowledge by actually going out and applying the techniques to more real world material, preferably in Python. The goal of this is to have something to show employers aside from just a class.
I have no illusions of spending a month working and being able to beat currency markets or whatever, but while I'm doing this, I'd like to test it on markets that aren't flooded with professionals and see what happens. I'm looking for resources/guides to get started - I'm not sure if I need data scrapers, need to set up a database etc. Basically just good resources to applying the stats I've learnt and possibly a primer on the finance I need to know.
Totally open to different directions I should go in. Apologies if this is a duplicate, I did try searching but mostly saw people hoping for a 'magic bullet' to crush markets. I'd be super happy with (optimistic I know) setting up some sort of auto trader for crypto markets even if it lost a bit, just for the experience.
edit: I should also add that I've done 5 computer science classes so am comfortable with programming in general, and have done a bit of stochastics through our stats department