https://greenteapress.com/wp/think-stats-2e/ https://greenteapress.com/wp/think-bayes/
I wanted things like design of experiments and hierarchical bayes methods, logistic regressions, and other somewhat advanced topics, and most of the things I found were poorly written R documentation. Which from a development perspective is too much effort to grok, read papers, and then port the code to python.
It really sucks that R is the go to for so much when deploying R in a production environment is a pain or not possible.
In any case, I would recommend skimming a lot of books and finding one that contains enough practice questions (with solutions) and is suitable for your level.
But probably the most useful thing was a college course where we implemented all the 101 & 102 level statistics algorithms in Excel, so you could see precisely what it was doing.
https://youtube.com/playlist?list=PL8dPuuaLjXtNM_Y-bUAhblSAd...
In particular, you might want to start with this 4-part overview, which comes with video lectures: https://nobsstats.com/stats_overview/README.html
I hope to finish the book by the end of this summer (the book itself won't be free, but all the notebooks and additional exercises will be free online at nobsstats.com)
If you're looking for other sources, you can check out this google document where I collect the best STATS101 learning resources: https://docs.google.com/document/d/1GWyuNC4qCL5ecYSoY6GxvuhO...
Good luck with your learning... it's not an easy subject (lots of historical baggage), but it's super important stuff.