Additional Resources

(for Data Science)

Many have asked me how did I learn (Python, R, LaTex, Git…). I want to share resources that I have used/heard good things about. Learning how to program for me involves a lot of online searches as well as trial and error. However, when I learn completely new techniques, I find it helpful to start with some structured online resources to understand basic concepts, hence, the list below hopefully can serve as a starting point for you.

R

I learned R from various classes at UC Berkeley, including Stat 133 and a DeCal class. Therefore, I don’t have personal experience with any online resources.

ggplot2

ggplot2 is one of the most popular plotting libraries in the R community.

ggplot2 documentation - Cheatsheet on the website is helpful for me

dplyr

dplyr introduces grammar of data manipulation to R and Data Science.

dplyr webiste

Shiny

Shiny is a popular R web application framework that allows you to build interactive web application using R and R syntax

Coursera - Developing Data Products - I have personally taken this class to learn about Shiny

RStudio Shiny Tutorial - I found the tutorial and gallery helpful

Python

I learned Python through UC Berkeley Data 8 class. - The class is now available through edX

Data Science/Machine Learning

Data Science is such a broad topic that it is hard to list resources. There are a few books that I think are great for beginners. I however did not learn from books. I learned mostly through work experience and projects.

R for Data Science

LaTex

I found codecogs helpful when looking for LaTex syntax

Git/version control

I learned Git through many trial and error. GitHub help page - I found the GitHub help page very helpful with the screenshots

Happy Git and GitHub for the useR - I have heard good things about the book, particularly targeting R users.