If you were to spend a year or so going through many of the resources presented here, and probably knew your stuff pretty well (or at least as well as you could after a year), would anyone actually give you a job?
Nobody is "given" a job; you "earn" a job by convincing the hiring manager that you can do what they need done.
If you're any good, and have good results to show and talk about, yes, you could totally be employed.
If you show that you're extra willing to do all the heavy data preparation and labeling work yourself as well as the infrastructure that runs the models, you'll have an even easier time. Most people just want to play with models, and believe data preparation is "beneath" them, but that's actually where the meat is and where the success of the model is made or destroyed.
It depends what sort of a job you have in mind. If you wanted the sort of job where you spend all day every day doing ML/DL/AI stuff then no, that's a pure research job and probably needs a PhD. But the life of an ordinary working data scientist isn't like that: you would spend 75% of your time acquiring and cleaning/pre-processing data (including all the organizational tasks of finding it and persuading people to give you it), 20% of your time trying to shepherd what you had created/discovered into a real, working production system, and maybe 5% if you are lucky on this sort of thing. You absolutely can learn everything you need to get to this level through MOOCs. The rest is down to your interview skills.
