Basics: RStudio education

Beginners may want to start with the most updated resources of R, like the tidyverse,
https://education.rstudio.com/learn/beginner
and then go into depth through references therein.

Shiny apps

From the very start of R towards Shiny web apps like a PRO
http://shiny.rstudio.com/tutorial/

Advanced students

Those students already acquainted with data science might prefer to start from the reference book R 4 Data Science
https://r4ds.had.co.nz/

Advanced R

The book Avdanced R (http://adv-r.had.co.nz/) provides an entertaining roadmap to some of the deeper
subtleties of the language and how to work with it most effectively.

R packages like a PRO

If you  might want to create and publish your own R package https://r-pkgs.org/

R community

Read R bloggers at https://www.r-bloggers.com/

R project for Statistical Computing

https://www.r-project.org/
CRAN mirror in Milan https://cran.mirror.garr.it/CRAN/

Documentation and tasks

Contributed documentation on basic R (several languages)  https://cran.mirror.garr.it/CRAN/other-docs.html
Task Views https://cran.mirror.garr.it/CRAN/web/views/
R Journal https://journal.r-project.org/

Bioinformatics

https://www.bioconductor.org/

R-related books to read

Please look at https://bookdown.org/

Writing your own book or report using R

https://bookdown.org/yihui/bookdown/

Build your websites using R

https://bookdown.org/yihui/blogdown/

R for Data Science at Coursera and projects

https://www.coursera.org/learn/data-viz-shiny-dashboards
https://www.coursera.org/specializations/data-science-foundations-r
https://www.coursera.org/learn/r-programming
https://www.coursera.org/learn/data-viz-shiny-dashboards
https://www.coursera.org/learn/using-r-for-regression-and-machine-learning-in-investment
https://www.coursera.org/projects/analyze-stock-data-using-r-quantmod
https://www.coursera.org/projects/manufacturing-simulation-r-simmer