# Online Course from Statistics.com: Advanced Programming in R

Hadley Wickham teaches “Programming in R – Advanced,” June 15 – July 13 online at Statistics.com. This is the third in a series of courses that cover programming in R, so if you are new to the subject you should start with our Jul 27 course “Introduction to R: Data Handling.”

Upcoming Courses:

- Jun 15: Advanced Programming in R (more below) http://bit.ly/rblog-advprog
- Jul 20: Visualization in R with GGplot2 http://bit.ly/rblog-ggplot
- Jul 27: Introduction to R – Data Handling http://bit.ly/rblog-data
- Jul 27: Introduction to R – Statistical Analysis http://bit.ly/rblog-stat
- Aug 31: R Modeling http://bit.ly/rblog-model
- Oct 19: Graphics in R http://bit.ly/rblog-graphics
- Oct 26: Programming in R http://bit.ly/rblog-prog

In “Programming in R Advanced,” you will hone your skills to work with a variety of data types and data sources in R. You’ll also learn some techniques for programming “in-the-large,” when you are trying to provide a suite of functions to flexibly solve a large class of problems. In particular, you’ll learn more about functions, environments and closures, and the basics of object oriented programming with S3.
Dr. Hadley Wickham is the author of “ggplot2: Elegant Graphics for Data Analysis (Use R)” and a contributor to Cook & Swayne’s “Interactive and Dynamic Graphics for Data Analysis: Using R and GGobi” (2007). His research interests include interactive and dynamic graphics, developing practical tools for data analysis, and in gaining better understanding of complex statistical models through visualization. An Assistant Professor at Rice University, Dr. Wickham has developed 15 R projects, and written numerous articles, chapters, and other papers and in 2006 he won the John Chambers Award for Statistical Computing for his work on the ggplot and reshape R packages. Participants can ask questions and exchange comments with Dr. Wickham via a private discussion board throughout the period.

Details and Registration
The course takes place online at Statistics.com in a series of 4 weekly lessons and assignments, and requires about 15 hours/week. Participate at your own convenience; there are no set times when you are required to be online.