It actually depends on what you want to achieve. For example, if you want to do research in DL, the best way is not to start with DL at all and instead do some fundamental math courses like LinAlg, Prob/Stats, Intermediate and Advanced Calc, etc., then turn to traditional ML, and only after that you do DL. This is the bottom-up approach and it is a long journey that takes years. But from your post, it seems that you are looking for a quick top-down approach. For that, I would suggest you simply look into some medium.com articles, youtube videos, udemy courses and most importantly the dive head first into coding (try running as many examples from github as you can). Try reproducing some basic results, like getting >90% accuracy on CIFAR-10 classification with a ResNet model. You could also try getting into a bootcamp if there's one going on nearby.