In most of the Data Science and AI articles, blogs and papers I read, the focus is on a particular algorithm or math angle to solving a puzzle. And that's awesome - we need LOTS of those.
However, even if you figure those out, you have to use them somewhere. You have to run that on some sort of cloud or local system, you have to describe what you're doing, you have to distribute an app, import some data, check a security angle here and there, communicate with a team....you know, DevOps.
I've done presentations and talks for DevOps in Data Science, and as part of that, I'm pointing to the Team Data Science Process (TDSP), something I've talked about here before.
The TDSP has a great github site, with just about everything you want to get started. I decided to make a Microsoft Project template for the process. You can download it here - (With all the usual disclaimers of use at your own risk, your outcomes may vary, all that "no liability" stuff - not sure how you could hurt something with a Project template, but hey, you can never be too careful. https://www.gnu.org/licenses/gpl-3.0.en.html
When you open the plan, you can click the link to the far left for the TDSP. Change the name and description of course, and add in any other Team Resources you need. The dates are of course incorrect - you'll need to estimate those from your experience.
Each task has a note - make sure you open those to see what resources we've already created for you.
Note that there is also a full set of templates you can use for Data Discovery, project documentation and more.
Oh, and for those of you who don't have Microsoft Project, I have an Excel sheet here with all the same data. You can pull that in to whatever tool you like.