- May 5: Mapping in R taught by Chris Brunsdon, (Director of the National Centre for Geocomputation, at the National University of Ireland, and the co-author of the R package GISTools) – take this f you’ve had some programming, or command line scripting.
- May 5: Graphics in R taught by Paul Murrell (Senior Lecturer in the Department of Statistics at the University of Auckland, New Zealand and author of Graphics in R) – take this course to get under the hood and look at core R graphics functions.
- June 16: R for Statistical Analysis taught by John Verzani, (City University of NY College of Staten Island and the author Using R for Introductory Statistics) – take this to learn R via your existing knowledge of basic statistics.
- June 23: Data Mining in R taught by Dr. Inbal Yahav, (a faculty member at the Graduate School of Business Administration, Bar-Ilan University, Israel, and co-author of the text Data Mining For Business Analytics Using R) – take this to learn how to partition data and use a holdout sample, how to measure the performance of predictive models, and what to do about the problem of overfitting.
- July 21: Visualization in R with ggplot2, first introduced at Statistics.com by Hadley Wickham and now taught by Randall Pruim, (Chair of Math & Stats at Calvin College, and author of the Mosaic Package for R) – Learn how to use the ggplot R Project to make, format, label and adjust graphs using R.
They have kindly agreed to offer R-Bloggers readers a reduced rate of $399 for any of their 23 courses in R, Python, SQL or SAS (a saving of $150-$200). These are high-impact courses, each 4-weeks long (normally costing up to $589). They feature hands-on exercises and projects and the opportunity to receive answers online from leading experts like Paul Murrell (member of the R core development team), Chris Brunsdon (co-developer of the GISTools package), Ben Baumer (former statistician for the NY Mets baseball team), and others. These instructors will answer all your questions (via a private discussion forum) over a 4-week period.
You may pick any of the R courses from their catalog page: