R, where should I start?

This is a dynamic post which I will continue to update whenever I find something new. Hope you will find the following links useful.

Online Courses for Learning the R language

1. Try R from Code School
2. Computing for Data Analysis by Roger Peng (Coursera)
3. Concepts in Computing with Data by Phil Spector (Berkeley)

Free Documentations for Learning the R Language

1. R for Beginners by Emmanuel Paradis
2. R Graphics by Paul Murrel
3. ggplot2 (official documentation)
4. Advanced R Programming by Hadley Wickham

Online Courses for Data Mining with R

1. Data Analysis by Jeff Leek (Coursera)
2. Data and Computing Fundamentals by Danny Kaplan and Libby Shoop (Macalester College)
3. Statistical Learning (Stanford OpenEdX)
4. CS109 Data Science (Harvard)

e-Books for Data Mining with R

1. R and Data Mining: Examples and Case Studies by Yanchang Zhao (Really useful worked examples!)
2. Data Mining Algorithms in R (Wikibooks)
3. The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman
4. Introduction to Data Science by Jeffrey Stanton
5. Forecasting: Principles and Practice by Rob Hyndman and George Athanasopoulous
6. Bayesian Computation with R (Free Kindle Edition): UK Link, US Link (Aug 2013 Update: No longer free)
7. 12 Free (as in beer) Data Mining Books

R Tutorials

1. Twotorials by Anthony Damico (learning new tricks from short 2-min videos)
2. Revolution Analytics Free Webinars
3. ggplot2 Graphics Cheat Sheet
4. 10 tips for making your R graphics look their best
5. Making Maps with R
6. Compiling R 3.0.1 with MKL support
7. Flowing Data - Tutorials
8. Quick-R
9. R-Uni (A List of Free R Tutorials and Resources in University Webpages)

Interesting Blogs and Articles

1. R-bloggers
2. Statistics Blogs
3. Whizage by Thia Kai Xin
4. R Resources by Vivek Patil
5. 100 most read R posts in 2012
6. "R" you ready?
7. The Angry Statistician
8. VizWiz - Data Visualization Done Right
9. FastML - Machine learning made easy
10. ggplot2 Blog
11. Spatial.ly - Visualisation, Analysis and Resources
12. Vistat - a reproducible gallery of statistical graphics
13. The Shape of Data
14. Animated Graph for Data People
15. is.R()
16. 60+ R resources to improve your data skills

Useful R Packages

1. Ten R packages I wish I knew about earlier (Before you do anything, read this blog post first!!)
2. caret (short for Classification And REgression Training) for a simple way to train and fine-tune model using different algorithms
3. ff and bigmemory - two packages to solve memory issues with big datasets
4. quantmod for financial modelling
5. foreach and doSNOW for parallel computing in R

Interactive Development Environment

1. RStudio - a really nice IDE for R
2. RStudio Server Amazon Machine Image by Louis Aslett (Wanna run RStudio on Amazon EC2? Try this!)

Other Useful Tips

1. Re-installing packages in R version 3.0.0

Data

1. UC Irvine Machine Learning Repository
2. Time Series Data Library created by Rob Hyndman
3. Quandl (like a Wikipedia for Time Series Data)