Center for Spatial Data Science, University of Chicago
April 12, 2019
9:00am - 4:00pm
Instructors:
Angela Li, Colin Quirk
Helpers:
Lilian Huang, Cecile Murray
General Information
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct
research. Its target audience is researchers who have little to no prior computational experience,
and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly
apply skills learned to their own research.
Participants will be encouraged to help one another
and to apply what they have learned to their own research problems.
Who:
The course is aimed at graduate students and other researchers.
You don't need to have any previous knowledge of the tools
that will be presented at the workshop.
Where:
Searle 240, Center for Spatial Data Science, 5735 S Ellis Ave, Chicago, Illinois.
Get directions with
OpenStreetMap
or
Google Maps.
Requirements: Participants must bring a laptop with a
Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges. They should have a few specific software packages installed (listed below).
on.
Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
Accessibility: We are committed to making this workshop
accessible to everybody.
The workshop organizers have checked that:
The room is wheelchair / scooter accessible.
Accessible restrooms are available.
Materials will be provided in advance of the workshop and
large-print handouts are available if needed by notifying the
organizers in advance. If we can help making learning easier for
you (e.g. sign-language interpreters, lactation facilities) please
get in touch (using contact details below) and we will
attempt to provide them.
To participate in a
Data Carpentry
workshop,
you will need access to the software described below.
In addition, you will need an up-to-date web browser.
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.
Note that if you have separate user and admin accounts, you should run the
installers as administrator (right-click on .exe file and select "Run as
administrator" instead of double-clicking). Otherwise problems may occur later,
for example when installing R packages.
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 dnf install R). Also, please install the
RStudio IDE.