Preparation before the course starts

Preparation before the course starts

In this class, you’ll learn the basics of R and GitHub, and how to use these tools to professionally working on empirical research projects.

It’s important to spend some time before the beginning of the class to install the required software, and familiarize yourself with R/RStudio.

1) Install R and RStudio

Throughout the course, we’ll use R - a comprehensive toolbox to handle and analyze large data sets. The best thing about R is that it’s open source. It’s freely usable by anyone. Plus there’s a vibrant community that keeps on developing R. Or extend it with your own packages.

  • Please install R and RStudio, by following these setup instructions.
  • If you’d like, you can also already start working on the R Bootcamp which we will cover in the first course week.

2) Get a GitHub account and install Git

Git is a file versioning tool - think of it as a combination of Dropbox (with unlimited & free rollbacks to previous file versions) and messaging client (to discuss projects with team members).

  • When signing up to GitHub, we recommend choosing a professional GitHub username (e.g., firstname.lastname, initial.lastname, etc.). Chances are high you are going to use your GitHub profile when applying for jobs.
  • Looking for a more graphical user experience? Then you may find GitHub Desktop useful as well.
  • Experiencing any issues to authenticate with GitHub (e.g., an error message about your password)? Head over to the support section for how to solve this issue.

3) Install make

During this course, we’ll be using Make - a tool used by software developers to automate workflows (e.g., to compile a new software program). Of course, we won’t write entire software programs, but instead work on our project pipelines (that consist of preparing and analyzing data).

  • You can find a tutorial for installing make here.

4) Get a good text editor

We recommend using a text editor, as this greatly improves your user experience and allows you to easily change text and code.

5) Get premium access to Datacamp.com

Finally, we’re borrowing some tutorials from Datacamp.com throughout this course.

6) Follow useful tutorials

  • New to R?
  • Never worked with the command line/bash/terminal?
    • Then please develop your command line (Windows) / terminal (Mac) skills
    • Check out the ( Datacamp tutorial - first chapter only)
    • Also check out this presentation about the command line / terminal.
      • Though it is targeted to Mac users, it provides a great overview.
      • Windows users could still follow along using the same commands by using Git Bash (or Cygwin).
      • The main goal here is to understand how directory structures work and how to navigate in the terminal or command line.
  • New to GitHub?

Next week