Despite what others day, no it isn't for math beginners that lack knowledge in calculus and linear algebra. His original machine learning class should probably come first for the absolute beginner.

Fast.ai is probably better suited for your purposes. I'd recommend that over ng if you lack math rigor.

If you want to learn math then progress through precal (axler), calculus 1-3 (stewart), linear algebra (strang and axler) and learn calculus based statistics and probability. Id recommend googling Berkely courses and following their pacing and problem sets. This is the bare min math you'll need and after you have this knowledge Ng class will be trivial. Id then learning real analysis and measure theory just to grow some hair under your arms but that is probably unnecessary studies for your purposes.

So in recap start with fast.ai and learn math through textbooks then Ng becomes trivial. If you then go on to learn analysis etc you'll start to become a mathematician and understand the theory better than most practitioners. But that is probably overkill for your needs