Hadley, of course, is the developer of the wonderful tidyverse set of R packages including ggplot2, dplyr, tidyr, readr, purrr, tibble, and many more. He is the author of several books including the new “R for Data Science”, he is the chief scientist at RStudio, and a fellow cocktail enthusiast.
From the course blurb:
This class will be a good fit for you if you have some experience programming in R already. You should have written a number of functions, and be comfortable with R’s basic data structures (vectors, matrices, arrays, lists, and data frames). You will find the course particularly useful if you’re an experienced R user looking to take the next step, or if you’re moving to R from other programming languages and you want to quickly get up to speed with R’s unique features.
On the first day, you’ll get a solid grounding in R programming techniques. We’ll start by reinforcing the foundations of your R knowledge, and then go on to cover the three main paradigms of R programming: functional programming, object oriented programming and metaprogramming. On the second day, you’ll learn how to make R packages, the key to well-documented, well-tested and easily-distributed R code. With the right tools, making a package is easy. In fact, it’s so easy that it will become your default way of organizing code.