Bring a laptop to the class every week if you have one. We encourage students to work collaboratively, so we would like to have at least one laptop for every 2 or 3 students. Since the homeworks and the project are the work of a team, we encourage you to team-up with students that possess a laptop. In the case you plan to buy a laptop, remember that the students from Swiss Universities have preferential prices via the Neptun Projekt or the EPFL’s Poseidon.

You do not need to buy a laptop if you do not possess one.

This class is based on the online textbook:

This document is under development and it is therefore preferable to always access the text online to be sure you are using the most up-to-date version. Due to its current development, you may encounter errors ranging from broken code to typos or poorly explained topics. If you do, please let us know! Simply add an issue to the GitHub repository used for this document and we will make the changes as soon as possible. In addition, if you know RMarkdown and are familiar with GitHub, make a pull request and fix an issue yourself, otherwise, if you’re not familiar with these tools, they will be explained later on in the book itself.

The textbooks below are also recommended and are legally available online for free. The following texts will be heavily referenced:

**Recommended**: Advanced R Programming by Hadley Wickham**Recommended**: R Packages Hadley Wickham by Hadley Wickham**Recommended**: An Introduction to R by W. N. Venables, D. M. Smith, and the R Core Team**Recommended**: blogdown: Creating Websites with R Markdown by Yihui Xie, Amber Thomas and Alison Presmanes Hill**Recommended**: R Markdown: The Definitive Guide by Yihui Xie, J. J. Allaire, Garrett Grolemund

The following textbooks are helpful, but not necessary to succeed in the course:

**Supplemental**: ggplot2: Elegant Graphics for Data Analysis (2nd Edition - GitHub Only) by Hadley Wickham**Supplemental**: R for Data Science by Garrett Grolemund and Hadley Wickham**Supplemental**: The R Inferno by Patrick Burns**Supplemental**: R Programming for Data Science by Roger D. Peng**Supplemental**: Seamless R and C++ integration with Rcpp by Dirk Eddelbuettel

We regrouped more references by category in the resources page.

All the software we will be using are free for acamedic activities. The course will use and present the R statistical computing language as well as different parts of C++ through Rcpp. The integrated developer environment that we will use to explore R is RStudio IDE made by RStudio Inc.