I mean it really depends how deep you want to go. Like you point out that the classes you took are 101 courses. These are really just "tasting" courses. I'm sur

I mean it really depends how deep you want to go. Like you point out that the classes you took are 101 courses. These are really just "tasting" courses. I'm sure if you decided to take more advanced/grad numbered courses, or unnumbered "topics" courses, you would have a better idea of what's going on. In general, "having a deep understanding of models & techniques in full detail" is not well-defined. For example, analysis of linear regression is often offered as a full year-long sequence for graduate students in math/stats depts. Is this necessary for doing linear regression in practice? Not really, but who cares - it's interesting stuff in its own right. Most people just need just enough understanding to finish a job. In general, the precise medium that you use to study something isn't that important as long as it works for you, but there is a good reason that there are longstanding classic textbooks that people swear by in most fields of mathematics. I do strongly feel that in the context of any mathematical subject, that there are few substitutes to the grind - doing proofs and solving problems on your own. Okay, but just to have at least one link in my post, I want to share this guy MathematicalMonk who used to make really great videos on ml-related stuff: https://www.youtube.com/channel/UCcAtD_VYwcYwVbTdvArsm7w https://www.youtube.com/channel/UCcAtD_VYwcYwVbTdvArsm7w