Appendix A — Resources for Learning R
To further your R learning journey, I would recommend a review of the following freely available resources. This list will constantly be updated as new material becomes available.
A.2 2. R Communities
- Posit (formerly RStudio) Community
- Stack Overflow R
- Stack Overflow RStudio
- Cross Validated
- R-bloggers
- R for Data Science Slack Group
- R User Community
- R-Ladies Global
- satRday
- rOpenSci
- Twitter (now X) – #rstats and #rstudio
- Reddit – r/rstats and r/RStudio
A.3 3. Conferences and Meetups
A.4 4. Cheatsheets
A.5 5. Tutorials
A.7 7. Data Visualization
A.8 8. Data Science
- R for Data Science
- Data 8: The Foundations of Data Science
- Introduction to Data Science
- Readings in Applied Data Science
- Elements of Data Science
- The Art of Data Science
- Data Science Cheatsheet
- Introduction to Data Science (for not-yet scientists)
- data.org
- Data Basic
- Data Science in a Box
- Data Literacy
A.9 9. Statistics
- An Introduction to Statistical Learning with R or Python
- Modern Statistics with R
- Introduction to Modern Statistics
- Statistical Thinking
- Introduction to Modern Statistics
- Biostatistics for Biomedical Research
- STA 212: Statistical Models
- STA 312: Linear Models
- STA 363: Statistical Learning
- Introduction to Probability for Data Science
- Statistics 431: Advanced Statistical Computing with R
- Statistics and R
- Tidy Statistics in R - Datamethods
- Statistical Computing
A.10 10. Datasets
- Awesome Public Datasets
- Dataverse Project
- Data Commons
- Open Africa Data
- Data Africa
- Our World in Data
- California Data Sources
- DataSF
- NYC Open Data
- The Humanitarian Data Exchange
- Global Data Barometer
- Microsoft Research Open Data
- Kaggle Datasets
- Google Research Datasets
- NHS R-community Datasets
- IHME
- Best Public Datasets for Health Data Science Projects
- World Bank Open Data
A.11 11. Tidyverse
- A very short introduction to Tidyverse
- Tidyverse Workshop Series
- Tidyverse Skills for Data Science
- Eight R Tidyverse tips for everyday data engineering
- Tidyverse Tips
- An Introduction to R through the tidyverse
- Modern R with the tidyverse
- C’est quoi, le tidyverse?
- Transitioning into the tidyverse (part 1)
- Transitioning into the tidyverse (part 2)
A.12 12. Programming: Functions, Loops, and Control Statements
- Control Structures
- Apply Functions
- Defining your own functions
- Functional programming 1
- Functional programming 2
- Statistical Programming Paradigms and Workflows
- Hands-On Programming with R
- purr tutorial
- Unlocking the Power of Functional Programming in R (Part 1)
- Unlocking the Power of Functional Programming in R (Part 2)
A.13 13. Machine Learning and Artificial Intelligence
- Hands-On Machine Learning with R
- Create machine learning models: An R version
- Interpretable Machine Learning
- Supervised Machine Learning for Text Analysis in R
- Posit AI Blog
- Tidy Modeling with R
- Tidymodels
- A Gentle Introduction to tidymodels
- The Case for tidymodels
- ISLR tidymodels labs
- Introduction to Machine Learning with the Tidyverse
- tidypredict