I recommend it. I feel I can now read an arbitrary paper, frown a lot, and eventually understand what it's talking about - to the point where I can implement my own buggy version. And hey, I built my own stable diffusion!!
I found the previous version of this course[1] to be a good complement: it's older (predates SD) but I feel it explains core concepts slightly better. Very understandable given how the close to the bleeding edge this new version is...
Perhaps an even better complement was Karpathy's famous course[2] - similar material but builds towards GPT instead of SD. The fastai coding style is somewhat esoteric (to me) so it was helpful to contrast with Karpathy's more familiar style. I recommend doing both courses. Also I believe the fastai folks are planning a part 3 which covers LLMs; looking forward to that.
Concepts from part 2 helped my hobby project, a 7-day forecast of renewable electricity and power price[3].
Feels pretty great to have built my own Stable Diffusion and GPT! I am grateful to Jeremy and Andrej.
[1] https://course19.fast.ai/part2