From Executive Summary page (page 2): Data Analyst role does not take data modeling tasks while ML Engineer does?
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From Executive Summary page (page 2): Data Analyst role does not take data modeling tasks while ML Engineer does?
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Amazing resource! It's so valuable that experts like you provide this information.
Many of these titles are getting confusing, and you will have different responsibilities in different companies. As far as I know, the Machine Learning Engineer (MLE) does not do data engineering, the MLE passes that to a Data Engineer (which is not included here).
Perhaps the problem is that these titles cannot be generalized across companies, and definitely not across differently sized companies. At a startup, you are most likely doing everything, while at Google, you are most likely doing one thing (or two, in some cases).
The best answer would be for them to just start own business.
Your the best teacher ever Sir. #AndrewYNg
Thanks for this great resource. Am I right in saying that your Coursera ML course prepares you for the ML Engineer role as per this doc?
Hi @JPOlivier — The Coursera ML course helps you build machine learning skills used in both data engineering, modeling, and deployment. However, MLEs also demonstrate skills in mathematics, data science, algorithmic coding, and software engineering. Does this help?
Thanks @AndrewYNg , but what about designers like myself? Do you view that as a different thing, i.e. not AI-related? Because, and without being a pompous twit, I do believe that people with human-centered design skills are much needed in AI development.
The current report focuses on science & engineering roles, but other roles such as product manager, project manager, or designer exist in AI teams. We hope to have a good answer to your question soon, stay tuned!
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