Ng's Deep Learning Specialization is awesome but I feel after this second course I need to stop and create my own exercises to build and apply NNs from scratch because I am learning how to convert math notation to vectorized Python code as much as anything else. I mean I am learning some core concepts along the way which I definitely appreciate and the reason I am continuing, but to become proficient I need to apply them without the hand-holding. Because those Coursera assignments have evolved to be computer-graded and easily approachable and so they actually do most of the thinking for you.

Also I feel the modern approach is not vectorized Python but something like Keras or Tensorflow 2 or anything that is maybe higher level or will allow me to keep the computation on the GPU/TPU and not going back and forth to the CPU like I assume numpy must be doing.