Python-bloggers

AI for Engineers

This article was first published on python – Win-Vector Blog , and kindly contributed to python-bloggers. (You can report issue about the content on this page here)
Want to share your content on python-bloggers? click here.

For the last year we (Nina Zumel, and myself: John Mount) have had the honor of teaching the AI200 portion of LinkedIn’s AI Academy.

John Mount at the LinkedIn campus

Nina Zumel designed most of the material, and John Mount has been delivering it and bringing her feedback. We’ve just started our 9th cohort. We adjust the course each time. Our students teach us a lot about how one thinks about data science. We bring that forward to each round of the course.

Roughly the goal is the following.

If every engineer, product manager, and project manager had some hands-on experience with data science and AI (deep neural nets), then they are both more likely to think of using these techniques in their work and of introducing the instrumentation required to have useful data in the first place.

This will have huge downstream benefits for LinkedIn. Our group is thrilled to be a part of this.

We are looking for more companies that want an on-site data science intensive for their teams (either in Python or in R).

To leave a comment for the author, please follow the link and comment on their blog: python – Win-Vector Blog .

Want to share your content on python-bloggers? click here.
Exit mobile version