PhD toolbox workshop is for any phD student who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.

We will cover the follow topics:

• Day1

  • Reproducible research

  • UNIX

• Day2

  • Introduction to R and R data.frames

  • Aggregating and analyzing data with dplyr

• Day3

  • Data visualization with ggplot2

  • Reproducible research with R

• Optional

  • Version control

Open-source

We will only use open-source software and all the course’s slides and materials will be publicly available on GitHub.

Wiki page

On GitHub there is a WIKI page with specific information for each day.

On the WIKI page you can also find useful links and extra contents.

All of the software required for this Data Carpentry workshop will be installed on the computers at our training venue.

Participants could bring their laptops. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.

However, if you want to use your own laptop, you will need working copies of the described software (R, RStudio, Git). Please make sure to install everything (or at least to download the installers) before the start of your workshop. We encourage participants to bring their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.

• We will use Etherpad for chatting, taking notes, and sharing URLs and bits of code.

• You have to create an account on GitHub:
  1. Go here
  2. Create a profile
  3. Write on the etherpad your name and your GitHub username
  4. The teacher will add you to the Student_2018 team!
  5. You will receive a confirmation email
  6. Click on the link in the email to see the conversation
• We will use sticky notes to assess the completion of the exercises or for asking questions. Sticky notes will be also used to evaluate each chunk of the course. This is a good way for the teachers to improve and help the students.