##Resources to help while learning R & Data Science This is an incomplete list created to assist in learning the basics of R and Data Science. Additionally this is not simply a list of books, the majority of links point to interactive resources.

####Command Line

• The Command Line Crash Course - This book is a quick super fast course in using the command line. It is intended to be done rapidly in about a day or two, and not meant to teach you advanced shell usage.

• ExplainShell.com - Write down a command-line to see the help text that matches each argument.

• Conquering the Command Line - This book is for new developers, experienced developers, and everyone in between who wants to master Unix and Linux commands.

####Git & Github

• Try Git - Learn how to use Git by reviewing the basic concepts of Git version control in an interactive online environment.

• Official Git Tutorial - The official gittutorial man page is a good place to start.

• Git Immersion - A guided tour that walks through the fundamentals of Git.

• Git Learning Videos - A small group of videos to get you started with Git version control.

####R & Data

• Try R - Learn the R programming language for data analysis and visualization.

• Introduction to R - In this introduction to R, you will master the basics of this beautiful open source language.

• Data Analysis and Statistical Inference - In this course you are introduced to the discipline of statistics as a science of understanding and analyzing data.

• Introduction to Computational Finance and Financial Econometrics - In this course, you'll make use of R to analyze financial data, estimate statistical models, and construct optimized portfolios.

• How to work with Quandl in R - In this interactive tutorial you will learn how to effortlessly pull any of Quandl's data into R for quick and easy analysis!

• swirl - swirl teaches you R programming and data science interactively, at your own pace, and right in the R console!

• The Beginner’s Guide to R - This 30 page guide will show you how to install R, load data, run analyses, make graphs, and more.

• Programming Exercises for R - Rich exercises for R, assumes R is installed.

####Other Resources

• R Markdown - The site provides a quick tour of the R markdown syntax, as well as in depth articles and examples.

• R Style Guide - This is how other R users will expect your code to look when you share it.

• R for Matlab Users - The site provides equivalent commands for users coming from Matlab / Octave / Freemat into R.

####Please Contribute! This list of resources was put together to assist in learning the R programming language and some Data Science. Please feel free to contribute in anyway! Whether that means providing your own content, creating a new category, adding new links, or simply correcting a spelling error. There are a few ways to contribute:

• Edit on Github - For small changes such as adding a link or correcting a spelling error.

• Issues - Open an issue and I'll take a peek and update.

• Pull Request

Fork this repository.
Add changes.
Commit your changes.
Submit a pull request.

If all else fails, feel free to contact me on twitter: [@tycrollins] (https://twitter.com/tycrollins) or email: hello [@] tyrollins.com

I will try and address contributions asap, or inform you if and why the contribution was denied.

Happy Studying!