How to get started with R programming Link to resources both free and paid. Roadmap Business Intelligence, Data Science, R Programming

1. How to get started
with R Programming
Ramon E. Salazar – Business Intelligence Professional

2. The case for R programming
• Almost all data science packages integrate with R, that’s why it is so important to use it. That includes our main
partner, Tableau.
• Additionally, R is free (open source), meaning that we could provide our consulting services even without
• Requiring the client to invest in a predictive analytical tool (if they do not have one)

3. Why Learn R?
Objective: Gain knowledge in the most popular programming language for Data Scientist. Being able to
Create a simple linear regression model with R.

4. R Studio
R Programming Language Libraries
In order to use R, you first need to learn R Studio. Please download from the two links below
R programming/ R Studio
Objective: Install and configure R development environment

5. Learning R Studio IDE and basics
Free options for learning R studio:
• R studio official online learning website with tutorials,
webminars and tips
• UCLA R studio tutorial
• Princeton R Studio Introduction (PDF)
• Introduction to R studio Free Video
Objective: Learning R studio and basic R

6. Pluralsight courses (paid)
Paid option for Learning R Studio (Pluralsight) Link to Rstudio course in Pluralsight

7. Advanced
• Understanding Machine Learning with R
• Mastering Data Visualization with R
Visualization
 Beginning Data Visualization with R
 Multivariate Data Visualization with R
Start with
 R Programming Fundamental
 Data Science with R
 Exploratory Data Analysis with R
Pluralsight has a good selection of hands-on R courses, listed below
Pluralsight courses (paid)

8. Books
One of the best books for R programming is

9. Hands on with commercial tools.
Objective: Complete at least one linear regression model using commercial tools: Spotfire, Alteryx and others..
Why linear regression? . From all the data science techniques, this is the easiest and most popular one.

10. In Tableau, Predictive analysis done via R integration.
Resource #1 White Paper “ Advanced Analytics with Tableau”
Link White Paper Advanced Analytics with Tableau
Link Tableau manual - Pass Expressions to R
Resource #2 – Video
Link Video Advanced Analytics with Tableau
Tableau (R integration)

11. Github-online community with code and
repositories

12. Kaggle-online community for Data Scientist