Again, what's the use of MSc+ level math in ML? A good BSc course teaches you in the 1st year linear algebra up to the eigenvalues theory, and diff equations up to fairly involved numerical methods. Just these two subjects are way more than necessary for applied ML.

I'd go even further and claim that ML has no theory on its own: it's a bunch of methods based on simple linear algebra. Unlike a proper math subject that begins with axioms, definitions and theorems, an ML course would have nothing like that. One shining example is convergence of an ML model: there is no theory that would predict convergence, so the only way is ad-hoc attemps to massage the data and hyperparameters.