January 23-24, 2016
9:00 am - 5:00 pm
Instructors: Naupaka Zimmerman, Jeffrey Oliver
Helpers: Karthik Srinivasan, Branden Lau, Sebastian Velez, Jonathan Strootman, Ashley Lawrence
Software Carpentry's mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".
Who: The course is aimed at graduate students and other STEM researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop. Day one of this workshop is targetted to those with no prior experience with R or programming in general. The second day is geared towards either those who have attended the first day or else have a bit more experience with R or programming. The first day will cover the basics of R and how to use it from within RStudio. The second day will cover more advanced topics of interest to the group. Intermediate or advanced learners may opt to only attend the second day of the workshop.
Where: 1500 E University Blvd. Tucson, AZ. Get directions with OpenStreetMap or Google Maps.
Requirements: Participants must bring a laptop with a few specific software packages installed (listed below). They are also required to abide by Software Carpentry's Code of Conduct.
Contact: Please mail hilgert@email.arizona.edu for more information.
Etherpad: http://pad.software-carpentry.org/2016-01-23-U-Arizona.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Software Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager (e.g. for Debian/Ubuntu
run sudo apt-get install r-base
and for Fedora run
sudo yum install R
). Also, please install the
RStudio IDE.