In my personal experience, this isn't a question of either/or, it's a question of order. That is, courses are fantastic, but most of the time, they're more bene

In my personal experience, this isn't a question of either/or, it's a question of order. That is, courses are fantastic, but most of the time, they're more beneficial after you've done some JIT learning. Fastai, who in my opinion create the best educational resources in the deep learning space, are a great example of this. They use a metaphor involving sports to explain their approach. You don't learn to play a sport by pouring over rulebooks and studying professionals—you start playing. However, as you get a feel for the sport, you then find yourself in a position where learning a lot more about the theory of the game would make a huge difference to you, and that's where courses come in. Similarly, they get you off the ground quickly with some basic intuitions around deep learning, give you a sandbox to do some JIT learning, and then begin layering in deeper concepts. I've had similar experiences in my life, where taking graduate level courses was incredibly rewarding specifically in areas where I'd already spent a decent amount of time doing JIT learning—and arguably, where I'd reached a relative limit in how far JIT would take me.