(particularly the Dexter Chua notes). This may be too hard without tutor support, but I figure I can always find easier material if it gets too tough.
If the former, I don’t see why you would go through a structured programme again, you already know what the knowledge tree looks like and you can google for the best textbooks or youtube videos for each topic or course.
What I studied during my cs course was just the basics: linear algebra, mathematical analysis, probability theory, and physics. All beginner levels.
I do need to refresh my knowledge from 10 years ago in order to move forward. I was thinking about taking the time off from work and spending a year in a library reading books and learning more. The problem is that I don't really know which direction to take, what are the good books for that. And this is something I hoped a university program would solve.
If you want to become a research mathematician through self-study, then working through the qualifying exam syllabus for an established math program could be helpful [1].
If you want practical skills in the fields you have listed, then a great way to get them is to work through Gilbert Strang's OCW linear algebra course and Feynman's lectures on physics. That means doing the problem sets, all of them. The former will give you linear algebra, the latter will give you useful analysis/probability/physics. If you diligently solve the P-sets, you will probably be in better shape than 99% of people leaving university with a BS/MS in math/stats/physics.
It is very easy to go down a rabbit hole that is not useful to a practitioner. This is particularly true in analysis and probability theory. Almost no one but a research mathematician needs to know about Lebesgue measures or Radon-Nikodym derivatives or whatever.
[1] https://www.math.harvard.edu/graduate/study-the-qualifying-e...
I'm not looking for a research career in maths but rather to refresh my existing knowledge and deepen it even further.
Thanks a lot for the suggestions.