[Discussion] Best way to learn AWS for ML applications?
Just to set the context: I have decent experience with ML, I can design models that are appropriate for the problem at hand, I can implement them in code (mostly using open source libraries, think scikit-learn, Keras, PyTorch, but I can and have implemented from scratch if need be) and I understand/can intelligently communicate the math behind them, but I think I’m ready to take the next step. I’m trying to make myself marketable for ML Scientist/Engineer positions, and it seems that most of them require some knowledge and experience with cloud services and/or distributed computing, e.g. AWS, Azure, Kubernetes.
Would learning AWS be the next best step here? Or would you recommend a different platform/service? If AWS is the best way to go, how would I best go about learning to use and understand all of its services? Note that I would be doing this on my own free time (not through my company). I know there is AWS free-tier, but will I be able to try out and practice everything that I need there? Next, what are some good courses for beginners? I’d like courses with exercises that I can follow along, not just explanations of concepts. Is picking out a good course and following along on a free tier instance the way to go? How did you “learn” AWS?