The homework is not checked or anything like this. Anything we do in this course is just for us - meaning you should do whatever you feel is helping you learn 
Part of what seems to work very well (as Jeremy suggests in the lecture) is running code, seeing how things change with changes to inputs, checking out the docs, playing our with jupyter notebook -> getting acquainted with the whole ecosystem.
This thread is about giving people a bit of a helping hand with what they can do for the first lecture to get going, but generally you can come up with anything you feel would help you learn (running the code on your own data or some other dataset - maybe even one built into fast.ai, this links to fastai v1 though, writing a post on the forum explaining something, asking a question, writing a blog post, creating a NB on something that interests you, pushing to github and sharing on the forums, etc).
I am not sure if it’s part of the top-down way of learning (didn’t read the book) but in the way the fast.ai courses play out, you control your destiny, or what you get from the course! Sounds very similar to life in that regard