It's pretty cool, you'll have fun! It's "practical" not "theoretical", so the focus is on getting code working and understanding bare minimum of math you need.
They are professionals, so they know "what it takes" to be good at the subject.
Machine learning math is not rigorous in comparison to the type of math you'd study as a math or physics major.
Machine learning math is useful precisely because of the fact that it shows you intuitively how the concepts work.
Knowing the "high level" ideas is near-useless. I can get the "high level" ideas of quantum mechanics from any high school or pop science physics book. Does that mean I know quantum mechanics? Only at an extremely superficial level.
And I suspect anyone taking a MOOC on AI or machine learning wants to end up with more than superficial knowledge.
I was mostly speaking about math professors in college. I have degrees in Math and EE...advance math isn't an issue.
Having abstract intuition (aka "high level ideas") in math is incredibly value.
Sometimes things get hairy in the computation and you need to step back and consider the bigger picture again.
If you don't understand how the math works then you don't have the intuition and vice-vera.