I learned by joining an early AI startup with some co-founders who knew about old-school AI (but didn't believe in backprob!), and then reading absolutely every ML paper I could find, following AI hotshots on Twitter, reading the darknet source code, and experimenting with pytorch.
Eventually two of us left to start Vertigo.ai, and found a customer who would fund a fast object detector to run on a $18 Nano-PI. That was a fun challenge and forces me to think about how to make the AI run fast and with relatively low footprint.
Today fast.ai might be a good starting point, definitely recommend going with pytorch, cloning cool projects from github, and going from there.
