I found value in this course, but to be honest... I think a MOOC is likely a poor way to learn math. After all, whatever you're learning (math, coding, whatever) your main learning time is when you're in the trenches solving problems, ideally with access to help when you need it. For CS stuff MOOCS seem great. A class based around what amounts to 10 problems (code up the feed forward and back propagate part of this neural network. Use this technique to predict this target variable with this data set, etc) all take a fair bit of time, and get you thinking about a lot of different sides of your craft.
Math on the other hand, it seems like most problems (until you're pretty high level at least) are going to be more run and gun. Your linear algebra will be solid when you've cranked through a few hundred problems covering different techniques, you know? So... what I've done, I picked out some textbooks with accessible solution manuals, a lot of useful practice problems (ideally more geared towards probing deep understanding instead of math busy work) and just... you know. Cranked through. I feel decent about my stats knowledge now, I'm currently working hard to shore up my linear algebra, heading towards matrix calculus. I got a ways into this and realized I need a little more background, haha.
Which brings me to my next thought... math is far easier for me to learn at least, when I have a concrete goal. I'm not actually all that interested in math as a thing in and of itself, but I'm extremely interested in anything that'll give me new insight when solving complex problems. You might find that you have narrow pockets of math you need to pick up now, and don't actually need to go through whole courses or anything.
If you need low level stuff though (basic stats, intro to linear algebra, basic calc, etc.) then Kahn's Academy's probably your best bet, but obviously you'll run way outside the course has to offer pretty quick if you're interested in getting into white papers and such.