I dislike learning from video (upping playback speed helps), I dislike the coding style of the library and the notebooks (nonlinear notebook execution especially), and I still think this is the best available class on anything deep-learning related, and it's only getting better. The top-down, practice-before-theory approach is excellent, but they still get into the theory, often in a much more intuitive and better motivated way than you get elsewhere. Also tons of little breadcrumbs dropped throughout lessons and in the forum to dig deeper for those inclined to.
If you go this route, make sure to follow the suggestion of re-implementing each lesson, from scratch, without referring back to the original notebook. It's a little too easy to not do that and miss out on the lessons you learn from struggling through the actual code.
Thank you for that suggestion.
I wholeheartedly recommend the fast.ai [0] course. It provides a lot of instantly applicable code, coupled with very good explanations which you can try out on novel problems later. It's focused on "learning by doing", and not "learning by reading" which fits my style really well.
That said, it doesn't dissuade the watcher from reading later, it's just not recommended to start out with.
[0]: course.fast.ai