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[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?

submitted by /u/rev_daydreamr
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.