R Programming
Learn R from the best R tutorials, including the most popular R online courses, videos, books, podcasts, and blogs.
R in Action
R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.
Beyond Spreadsheets with R
Beyond Spreadsheets with R shows you how to take raw data and transform it for use in computations, tables, graphs, and more. You'll build on simple programming techniques like loops and conditionals to create your own custom functions. You'll come away with a toolkit of strategies for analyzing and visualizing data of all sorts using R and RStudio.
R: Interactive Visualizations (Linkedin Learning)
Start by learning to manage packages and structure data for visualizations with the tidyverse and the pipe operator. Then there is an important question: Which library should you choose? The course introduces five popular options: Leaflet, Plotly, Highcharter, visNetwork, and DataTables (DT).
R for Data Science: Lunchbreak Lessons (Linkedin Learning)
Programming is learned in small bits. You build on basic concepts. You transfer the knowledge you already have to the next language. Lunch Break Lessons teaches one of the most popular programming languages for data analysis and reporting'in short lessons that expand on what existing programmers already know.
R Programming (Coursera)
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.
Learn R (Codecademy)
In this course, you'll be exposed to fundamental programming concepts in R. After the basics, you'll learn how to organize, modify and clean data frames, a useful data structure in R. Then you'll learn how to create data visualizations to showcase insights in data! Finish up with statistics and hypothesis testing to become a data analysis expert.