raab

SageMaker has three parts. Hosted notebooks, similar to case #2. API access to ML algorithms which are "optimized" and deployment by providing API access to trained models.

Cool! I had never heard of that. Starred...

I would agree, most data scientists are not required to deploy their own models, probably only for those in startups or small companies. I also introduce how Docker can be used for development. I think it is a big enough trend in CS that any data scientist should know some basics, similar to data science from the command line.