1.  -- Programming language for statistician by statistician 

2. -- IDE for R

3.-- Data Visualization Tool

Make account on 

1.  --  Distributed revision control and source code management

2.  -- Markdown(HTML, pdf report from R) hosting site

3.  -- Hosting your Tableau public workbook.

Once everything is set up open R studio and choose which R version you want to use whether 64bit/32 bit (you can change version later from R studio if you want) choose 32bit as 64bit has some issue while using  package like mailR, ODBC etc. You can change to 64bit version when you need from Rstudio UI. 

Once everything is step up go through few basic tutorial on YouTube or Datacamp.

Few best resources to learn basic of R:

1. TryR

2. Datacamp -- play and learn R

3. The Analytics Edge | Edx -- Edx course, its very very useful 

4. R-programming | Coursera -- Learn from fundamental  

5. R-bloggers --  Content collected from bloggers

6. R_books -- list of all useful R book.

4. Online-learning_R -- Blog post 

Advice: Don't try to be export(i.e  learn everything)  before writing program, after learning basic, try to write code that helps you in your work, you will write shit code ( when i see my old code I feel that too) but you will learn very fast. 

If you are not able to solve anything just google it, you will find solution. You will find solution to simple problem like changing col names to writing complex loop in google, always give it try.

List of most useful packages in R

1. dplyr, tidyr, reshape2, stringr  -- Data manipulation( sqldf if you know SQL)

2. ggplot2, pploty, googleVis, htmlwidgets , shiny-- Data visualization 

3. Markdown -- Reporting

Just play around with few packages, you will get hooked to them as they make you life so easy. Just few line of code and you will have beautiful visualization , cleaned data and summary of data.

Now we are all set to start automating and producing beautiful /lucid visualization.