My guess is that part 2 will provide a lot of these answers I have not touched optimizers apart from maybe changing hyperparams here and there since I started doing the courses, not sure there is any need for that.
For me, what I want, are just simple things - reading in the data how I would like to (images, tabular data, you name it), creating custom architectures and using whatever I want for labels, I think that takes me 99% along the way on my wish list
I think maybe understanding pytorch a little bit better helps to raise the curtain a little bit on what is happening… not sure.
Despite what I wrote above (maybe I was not very clear there) I no longer feel the need to understand everything… which is a very nice side effect of taking the fastai courses I just want simple building blocks I can hook up together, train a model here and there, and move on with my life
So to answer your question more fully - I think both reading custom data and modifying architectures is coming in part 2 And if you can’t wait there is a lot of that in part 2 v2 and in the machine learning course (but this uses fastai v0.7 I believe).
I would venture a guess part 2 + practice would be a short and correct answer to your question