By reading books like the one submitted, and doing your own small projects?

It's not that different from learning how to program without already having a programming job.

(That isn't to say either of these two is easy. They both require a lot of dedication.)

If your goal is to get a job, set realistic expectations.

There's a tiny job market for that - in comparison to, say, web dev - and these projects require professionals with very deep knowledge. This is not the kind of work where chatgpt or stackoverflow will help you a lot.

Side projects or working on other people's side projects. The most important things is to connect with the community and learn the technical language to speak with them. This is a relatively small community and you need bunch of different stuff to get started, some ML, coding for sure, some knowledge about how modern accelerators work, some skills to read and understand papers in this direction.

In my experience, best thing is to do side projects. Don't just learn a technology -- pick a doable project that leverages a new technology that you want to learn, and tackle it. Picking something "doable" is often the tricky part, so don't be afraid to re-evaluate after a few weeks and adjust your expectations as needed.

Important thing is to keep moving.

Do the fast.ai course, with a bit of elbow grease and creativity you'll be able to finetune models to produce SOTA results in >2 weeks.