- Description: Provides a thorough overview of programming in R.
- Instructor: Maxim Fedotov
- You must install R (https://cloud.r-project.org) and Rstudio (https://www.rstudio.com/products/rstudio/download/#download)
- If you are not familiar with R, you may complete the swirl tutorial. This is an R package that turns the R console into an interactive learning environment. You can easily install it by entering the following command in the R console:
install.packages('swirl')
After installing, run the following command
library(swirl)
which loads the package. Finally, run
swirl()
to get started with the tutorial and follow the instructions given there. If you are already familiar with R you may skip this step. The important part is that you get some basic familiarity with the language before the course starts. Other good tutorials you might want to follow are from DataCamp or Coursera.
This repo is structured as follows. First, you will find all handouts/lectures in the handouts folder. As a rule I will give handout in pdf and html format - I recommend using html ones, they look nicer. These files are generated from Rstudio, using the Rmarkdown package; you can find the source files in the same folder. Source files are usually better if you want to copy-paste some of the code, since these are text-files, without any formatting (unlike pdf or html). There is also resources folder where I will be putting useful things related to the classes - snippets of the code, articles etc.
Lectures are organized in a way so that the most of the time is spent learning-by-doing. Folder exercises will contain problems you will focus on during the class.
Exercises in this repo do not have autograde. Please see the README.md file in the exercises folder for more details.
All files you find in this folder come with a licence. LICENCE file describes in what ways you can use them further down the line, after the classes are over. The original licence is located here.
I am truly indebted to Hrvoje Stojic, who originally created these materials for several offerings of the brush-ups in Data Science, and Jordi Llorens, who was teaching the brushup in the previous years and adapted these materials. This repo is re-adaptation of these materials.