IMO, for reaching PhD eligibility level at ML, you just need 2-3 core math courses. (as long as each is rigorous) Linear Algebra, Probability and Statistics.

IMO, for reaching PhD eligibility level at ML, you just need 2-3 core math courses. (as long as each is rigorous) Linear Algebra, Probability and Statistics. (and some optimization) The fast.ai course is great, but having the math background really helps bring the whole field together. Different ideas and models with the math, seem to stand completely independent of each other. As a software engineer who wants to learn ML, the fast.ai course is great. But, if you find yourself in a situations where you are scoping out a data science problem, the math background helps immensely in coming up with a solution.