Must Love Data Mondays: Summer of Data Science

Since February, I’ve been completing a self study in data science.  The reason I decided to head down this path is because I feel like it’s been a natural progression from Quantitative Analyst to Programming.  I think it’s a natural progression and eventually all high level analysts will need to be some type of data scientist so I better start acquiring the skills needed now.

In the most recent Data Elixir Issue 37, has a link for that lists all the ways to learn Data Science over the summer there is even a hashtag created by Renee M. P. Teate which is #S0DS.  My goal for the summer is to become a data scientist while that may not be achievable through one summer of education I at least want to be on the path by continuing my education and complete some of my own research projects.  During this week, I’m going to write my curriculum for the summer and post it here for next week’s Must Love Data Mondays.

My rough idea for the curriculum is to focus on three areas over the summer:

Programming: I want to fully learn python and focus most of my data science work in Python.  I’ll also be taking a course in R to refresh knowledge because their seems to be a lot of opportunity for data scientists with R programming experience.

Statistics/Math: Refresh and Expand my knowledge of Statistics by choosing one of the available MOOCs starting in June.

Data Science: Continue to learn about the expanding field through books and online courses.

Check back next week to see my curriculum for June, July, and August.