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Rocio Ng edited this page Oct 4, 2018 · 61 revisions

Data Science Educational Resources

NOTE: If you would like to suggest a resource to be added to this page please send a DM to Rocio on Slack with a link to the tool and a short description.

  • Please limit suggestions to resources you have had some experience using
  • If there is a specific topic you would like to see covered here please let her know as well. This page is a work in progress!



  • swirl: Learn R, in R
    • Neat interactive way to learn how to do many things in R
  • R for Cats
    • Being a cat/cat-lover not a strict requirement. Introduction to R for complete beginners
  • R Cookbook
    • Useful Guide with lots of Examples
  • R For Data Science
    • Companion Website to Book by Hadley Wickham and Garrett Grolemund
  • Data Science with R
    • Companion Website to the Book with the same name
  • Stat 133 at Berkeley
  • Advanced R Hadley Wickham's interactive companion for his Advanced R book. If you want to learn how the language actually works (including its weirdo 3-teired OO framework and what's really going on with its lazy evaluation), go here. The metaprogramming aspects are extremely useful (code that writes code!).



  • Python for Data Analysis by Wes Mckinney
    • Great resource for learning how to work with the data analysis tools in Python

Data Processing and Cleaning

  • Getting and Cleaning Data
    • Important Class. Even if you don't code in R you can follow the examples and understand the proper methods and BEST PRACTICES for data processing
  • Introduction to reshape2
    • reshape2 is one of the most used packages for transforming data between long and wide formats. Useful to follow along to understand some fundamentals of data transformations

Machine Learning



  • Introduction to Statistical Learning by by Trevor Hastie and Rob Tibshirani - free e-book
    • Must-read for anyone interested in Machine Learning and aimed at a less mathematically inclined audience
    • Has useful labs that can be completed in R
  • Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman - free e-book
    • For anyone who wants an advanced treatment of machine learning models and methods
  • Hands-On Machine Learning with Scikit-Learn & Tensoflow by Aurelien Geron paid-book
    • Great overview of ML algorithms with accompanying code & applications in Python that you can practice with

Articles/Blog Posts


Probability & Statistics


Natural Language Processing


Deep Learning

  • Deep Learning
    • Free Online Textbook by Ian Goodfellow, Yoshua Bengio, Aaron Courville
    • Intro Chapters also cover a lot of the math needed for Deep Learning Models


Useful Blogs/Sites to follow

Awesome Studies for Inspiration

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