I was just beginning to give it a try, it just requires you to type the code that is shown on video. Poor way of teaching something, it seems at first. I sense this course is just to teach me the tools of the trade, not really enabling students to fully understand what they're doing.

On the other hand, some months ago I watched the ML course by Andrew Ng, and I still did not understand how to test a simple linear regression for myself, so I did not really understand it, and stopped watching the course.

From the yc reading list 2015 [http://themacro.com/articles/2015/12/yc-2015-reading-list/], they recommend [for Neural Networks] this book: http://neuralnetworksanddeeplearning.com/

It's more about understanding than "learning tools."

I really liked the NN&DL course. Another I've been meaning to check out is this book: http://www.deeplearningbook.org

That's an exceptionally clear, well-written book, and I recommend it without reservation. And it's free online, so anybody who's curious can just check it out.

NN&DL is great for neural nets specifically, it doesn't really cover other branches of ML. That being said, I found it very easy to understand with no prior ML knowledge, all you need is some calculus and linear algebra experience.

Could you share a link to the YC reading list 2015 . I'm surprised no one asked.

You might like the book 'data science from scratch' by Joel Grus. He uses Python without ML libraries and explains clearly what's going on.