Writing Efficient R Code

Benchmarking is measuring how long your R code takes to run so you can identify slow sections. The first chapter teaches you techniques to time your code accurately.

Code profiling identifies bottleneck lines in your script. You will use the profvis package to visualize exactly where your code spends the most time.

Yes. The final chapter shows you how to use multiple cores on your machine to run R code in parallel, significantly speeding up problems that can be split into independent tasks.

You should have completed Introduction to R and Intermediate R. Comfort with base R data structures, loops, and apply functions will help you get the most from this course.

Yes. Chapter 2 teaches you that many R problems have multiple solutions, and some can be orders of magnitude faster. You will learn which base R patterns to prefer for speed.