I guess universities shouldn't be forced to give open courses, but it is a fantastic thing that US showed was possible and I hope that more UK universities follow suit.
My understanding is that, like many MOOCs, it is largely department/faculty driven rather than a strategic or philanthropic move by the university overall.
I understand what I described above is a subset of ML, and I generally do agree with you that a solid background in probability and stats is important for people who plan to do a lot of ML.
Note - another possible objection here is that all "STEM" fields require calculus through differential equations and linear algebra. That's pretty much the common thread for most majors generally grouped together as STEM fields. So calling this "mathematics for machine learning" could be a little strange. If we're going to call vector calc and linear algebra "mathematics for ML", why aren't we calling it "math for physics", or "math for engineering"... I think that part of what is going on is that ML has gotten very popular, and people are starting to ask what the essential math background is, and are discovering that it's, well, pretty much the two year science and engineering track calculus you'd take at most universities.
This definitely isn't sufficient for machine learning, but it is a start.