The MBA Data Science Toolkit
Editor’s note: this blog was written and published by Daniel McAuley. You can read the full post here.
EXCERPT:
I recently had the pleasure of speaking on a few panels about analytics to my fellow MBA students and alumni, as well as many Penn undergrads. After these talks, I’ve been asked for my advice on what the best resources are for someone coming from the business world (i.e., non-technical) who wants to develop the skills to become an effective data scientist. This post is an attempt to codify the advice I give and general resources I point people towards. Hopefully, this will make what I have learned accessible to more people and provide some guidance for those who realize that the future belongs to the empirically inclined (see below) but don’t know where to start their journey to becoming part of the club.