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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!

General

R

  • 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

Books

  • 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

Courses

Books

  • 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

Misc.

Probability & Statistics

SQL

Natural Language Processing

Spark

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

Misc

Useful Blogs/Sites to follow

Awesome Studies for Inspiration

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