I think if this is more the fundamentals for AI rather than "this is all you will ever need to know", in other words NOT vocational, then this makes a lot of se

I think if this is more the fundamentals for AI rather than "this is all you will ever need to know", in other words NOT vocational, then this makes a lot of sense. When I started counting off the prerequisites to know what you are doing in ML, I could see it filling up a few years of coursework. Calculus up to multivariate calculus (gradient descent), a semester or two of statistics (gotta understand precision / recall, expectation, moments, marginalization), some programming (how are you going to implement your solution?), the fundamentals of regression (overfitting, cross-validation, regularization), don't forget linear algebra. Then there's some prerequisites for unsupervised learning like expectation maximization. SVMs? You'll be needing some constrained optimization and some applied math to make/understand a reasonable solver. This seems like the greater part of an undergrad degree.