Sure:) Perhaps I should have made clear that I was referring to the fact that CS231N follows the recommendation in the blog post - i.e. lots of exercises where

Sure:) Perhaps I should have made clear that I was referring to the fact that CS231N follows the recommendation in the blog post - i.e. lots of exercises where you implement things in primitive Numpy - rather than a broad "it's a better course". CS231N is frustrating in the real-world respect, although you're given some general recipes e.g. use ReLU, use Adam, etc. That said, I'd be interested to see some actual results from people taking what they learned in fast.ai (with no prior knowledge)and applying it to a new test set. It's easy to be impressed with the examples where you're walked through it, but figuring out what works on your data is whole new kettle of fish!