| Given the uncertain job market in ML/AI, I would recommend taking a few online classes aimed at practical applications. If you are a full stack developer working at a company you like then perhaps there are opportunities to add value writing simple models with available data that would be valuable to your employer? Sorry if I sound jaded in those comments, but I have mostly been employed as an AI practitioner since 1982 and I have seen severe cycles of plentiful AI work and little available work. I really recommend having a generalist’s mindset, and adding data prep/model building/deploying models as yet another skill. I mostly use deep learning now, and Andrew Ng’s online classes are very good. If you just want to have fun, you can read all of my recent AI books on my https://markwatson.com site, but to be honest I do less teaching of fundamentals and more just offering fun small programming experiments. In addition to Andrew Ng’s classes (still on Coursera?) I have found https://www.edx.org/ classes really useful and most can be taken for free. I also recommend signing up for OpenAI’s APIs. I spend very little money for a lot of use, and I have all but given up writing my own NLP code, something I have been doing off and on for over 30 years. I have a difficult time imagining what the future AI work landscape might look like for you but my guess is that tooling and applying new theories will keep getting easier and more people will at least have ML on their resumes. This is why, for both employability and work enjoyment, I recommend the generalist mindset. |