Berlin, 17-21 June 2019

Free University of Berlin

R is the most used data science software in the world. It is free, open, and potentially powerful.

Despite these benefits, many avoid R, struggle with it, or never quite unleash its power. This is because writing computer code to do any operation –a requirement in R– is at first both difficult and intimidating. Beginners often get lost when facing the diversity of functionalities, dialects and online material. Worse: many long-time users never really grasp how R works. As a result, they keep bumping into problems they cannot solve and thus remain dependent on others to move forward.

This course aims to help participants overcome those challenges by providing solid basics in R, through a well-balanced combination of guided exercises and explanations about how R works. Irrespective of their current level in R, at the end of the course, participants should feel much more at ease writing R code for the entire spectrum of a data science workflow: reading, editing, plotting, and analysing data, as well as shaping the results for publications.

The course will take place over five days. Students are free to bring their own datasets to work on.

This course is aimed at anyone planning to work with data regularly. It should be perfect for young quantitative scientists (e.g. biologists, psychologists…) who have not yet worked much with data, and also for those who have a long experience of working with data but who do not know R or  do not feel at ease with it. We welcome both people from academia and those working in businesses. The course has been created for individuals with little or no computer science background; no previous experience with R is required.

Note: a laptop able to connect to internet is required.

Monday -Classes from 9:30 to 17:30

 RSTUDIO day

After briefly introducing R and installing everything we need, this first day will be dedicated to learning how to use RStudio efficiently. RStudio is the most popular interface for R. I will explain how to use RStudio to set up the right options for R, install and update R packages, explore the R documentation, create projects to organise one’s work, write notebooks that keep track of the workflow, and more.

Application deadline is: May 18^th, 2019.