References

A very short R introduction

Big Book of R, by Oscar Baruffa. A bookdown bookmarking links to everything R for data science, from basics, visualization, tidyverse to distributed computing, spatial data science, machine learning, and more. GitHub

A Complete Tutorial to learn Data Science in R from Scratch - Basics of R, with short and conscise examples

teach-r - List of Resources for Teaching R

List of courses teaching R

The learnr tutorials in RStudio Cloud primers, avaliable on RStudio Cloud

swirl - R package for interactive R leaning

FasteR - Fast Lane to Learning R, learn R language in R console by following examples, by Norm Matloff

Hands-On Programming with R - introductory book how to program in R, with hands-on examples, by Garrett Grolemund

R for Data Science - a Tidyverse-oriented introduction to R online book, by Garrett Grolemund and Hadley Wickham

Advanced R and Advanced R Solutions - Advanced R programming, book and solutions, by Hadley Wickham and others

R Cookbook, 2nd Edition - statistics-oriented R introduction, by James Long and Paul Teetor

Efficient R programming - advanced concepts for efficient (R) programming, by Colin Gillespie & Robin Lovelace

RMarkdown from RStudio - illustrated guide to RMarkdown

Rmarkdown for Scientists book by Nicholas Tierney. GitHub

Mastering Shiny book by Hadley Wickham. GitHub

Yet another ‘R for Data Science’ study guide, by Bryan Shalloway. Tidyverse-oriented introduction to R

One Page R book “Data Science Quick Start: Knowledge Discovery Through R” by Togaware, includes pdf slides and R code templates for various machine learning tasks

Data Analysis and Prediction Algorithms with R book by Rafael Irizarry. Data science, statistics topics in R. GitHub. Old version, Labs, and Videos

R & Bioconductor Manual - One of the best R manual to brush up all major steps in data analysis/visualization. And links to other resources there. By Thomas Girke, UC Riverside

RProgrammingForResearch - course notes for R Programming for Research. R learning from ground up to tidyverse, with lectures, homeworks, data, source files

biostat561 - Computational Skills for Biostatistics, from version control, R programming, ggplot, shiny, to Unix, LaTeX, Markdown, Python. By Amy Willis

THRIV datasci 2018 - THRIV Data Science course by Stephen Turner. Comprehensive coverage from R/RStudio introduction, RMarkdown, dplyr, ggplot2, shiny to all practical and statistical aspects of data cleaning, visualization, predictive modeling, survival analysis. Workshops

Introduction to Data Science by Rafael Irizarry and Stephanie Hicks. The GitHub repo https://github.com/datasciencelabs/2020 has the latest course material, previous material for the course is available by changing the year number, e.g. https://github.com/datasciencelabs/2019. Data for the course

R Programming for Data Science by Roger Peng. Fundamentals of R programming and data science. GitHub

Mastering Software Development in R, book by Roger D. Peng, Sean Kross, and Brooke Anderson. From R basics to package development

Statistical Computing - Biostatistics 140.776 course by Roger Peng. Youtube Playlists

DataScienceSpecialization - Course materials for the Data Science Specialization from JHU folks. Detailed lectures on each topic

ds4stats - Data Science for Statisticians Workshop. Tidyverse, Data wrangling, visualization, ggplot2, machine learning. Rmds, lab exercises, links to ready-to-view lectures.

master-the-tidyverse - the Master the Tidyverse Workshop, tidyverse-oriented tutorials. Instructor material

Statistical Inference via Data Science, A ModernDive into R and the Tidyverse - bookdown, statistics and data science using tidyverse. GitHub

Statistical Thinking for the 21st Century - bookdown, statistics theory illustrated with R. GitHub material

R (BGU course) by Jonathan D. Rosenblatt. From R basics to regression, machine learning, graphics, shiny, advanced computing. GitHub

online-courses - Free courses by RSquareAcademy. From data import to tidyverse, web scraping, regex, databases. Videos, slides, code, data.

SISBID - several modules covering various aspects of data science. Summer Institute in Statistics for Big Data. Lectures, exercises, data. Module 1, Big Data, Module 2, Visualization of Biomedical Big Data, Module 3, Reproducible research, Module 4, Module 5

Ted Laderas and his Ready for R course, the accompanying Ready for R: Notebook Reference bookdown, and the R Bootcamp tidyverse exercises

R Programming For Research course by Brooke Anderson, Rachel Severson, and Nicholas Good, Colorado State University. Basic, intermediate, and advanced data analysis in R. GitHub, Youtube playlist with short videos on R-related topics

rstudio.cloud - a web-based instance of R/RStudio. RStudio cloud cheatsheet and notes, from Twitter source. RStudio Cloud for education - Mel Gregory - 24 min video with all the essense of using RStudio cloud for education

Tips how to configure RStudio

library(help = "datasets") - shows built-in R datasets

A list of over 1,000 datasets available in R packages, curated by @VincentAB. https://vincentarelbundock.github.io/Rdatasets/datasets.html