Hello TCU students! This repository will be the home to all the materials we will be covering in Dr. Preston's BI class. You'll have access to these materials in class via a web browser (via Amazon Web Services, for those who are curious), but feel free to clone/download this repo to your personal computer as well!

CRAN is where you go to install R. Google how to install it and all of the top hits will get you what you need.

RStudio is where you go to install... RStudio. Pick the one on the left that says it's free (they also make premium versions of RStudio as well as other products. You all will be using RStudio server in the classroom so nothing has to be installed on the lab computers.

It is not feasible to learn R in only an hour or two of a classroom setting. If you are interested in learning more about R, then feel free to check out these free resources:

• Data camp - some content might not be free
• Data Science track in Coursera (this is how I started - you'll have to audit courses for free access)
• R for Data Science
• Text Mining with R
• Github - I made this link to the "top trending R repositories" - it's always good to see what people are working on
• Kaggle - data science competition website. This is a great community for learning the basics as well as discovering new strategies for taking on unique problems. reading other peoples' scripts on this site is one of the best ways to improve your skills.

• Linux -- many web and data science tools only run on Linux; and if you want to deploy anything you build, you'll likely need to know at least the basics of linux
• Cloud providers -- I'm using AWS for these environments you all will be using
• Python -- not all problems are best solved in R