Currently a PM in the analytics space for last 3 years and I have had enough of it. Tired of politics and sitting in useless meeting all day without any meaningful work ( there are few meetings which I enjoy though where the discussions are technical). I was SDE before and have CS degree. Looks like I will be better of being a technical guy only and hence I want to transition into DS/ML space. Here is the plan that I have put together. Can you review it and give your suggestions ( anything i need to add/remove etc). Step 1: learn linear algebra ( took classes in undergrad but it was like 15 years ago) Step 2: learn probability and statistics Step 3: brush up on my python skills( my overall coding skills have become rusty since I transitioned into PM role) Step 4: brush up on Data structures and algorithms Step 5: take classes on Coursera/udacity related to DS/ML Step 6: learn scikit learn and tensor flow ( I am newbie so not sure this is applicable or not but this is something I have been hearing a lot) I know I will have to grind through CTCI and leetcode but I want to brush up my concepts first. I will also take part in Keggle competitions where I can apply some of the concepts that I learned Intel also offers some in house training on some of these areas and I will take those classes after going through the basics first Thanks fellas..!!
80% of work is dumb data shoveling. being smart about querying very large datasets + SQL or not - could help a lot.