So this is a common misconception about the text (and Prof. Mohri's NYU class). In this case, "foundations" does not mean this is an introductory course. Rathe

So this is a common misconception about the text (and Prof. Mohri's NYU class). In this case, "foundations" does not mean this is an introductory course. Rather, the class and text provide mathematical foundations for understanding the error bounds and growth complexity of various learning algorithms. So you'll be workin with convex optimization, reproducing kernel Hilbert spaces, and Rademacher complexity--definitely not "introductory" in the least! It's a completely different beast from Mitchell, Bishop, or EoSL (which I'm studying right now!), so I'm not sure comparisons are valid. It also fills a prominent gap in the ideas reviewed by the popular ML texts.