Online
May 13-14 2024
09:30 - 17:00
Instructors: Kashyap Chhatbar, Daniel Barker, Chris Wood
Helpers: Simon Harnqvist, David Kacs, Gabriel Rodríguez Canal
The Carpentries project comprises the Software Carpentry, Data Carpentry, and Library Carpentry communities of Instructors, Trainers, Maintainers, helpers, and supporters who share a mission to teach foundational computational and data science skills to researchers.
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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.
For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".
This is a pilot workshop, testing out a lesson that is still under development. The lesson authors would appreciate any feedback you can give them about the lesson content and suggestions for how it could be further improved.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: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.
When: May 13-14 2024. Add to your Google Calendar.
Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).
Accessibility: We are dedicated to providing a positive and accessible learning environment for all. We do not require participants to provide documentation of disabilities or disclose any unnecessary personal information. However, we do want to help create an inclusive, accessible experience for all participants. We encourage you to share any information that would be helpful to make your Carpentries experience accessible. To request an accommodation for this workshop, please fill out the accommodation request form. If you have questions or need assistance with the accommodation form please email us.
Contact: Please email c.wood@epcc.ed.ac.uk for more information.
Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.
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.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Please be sure to complete these surveys before and after the workshop.
Before starting | Pre-workshop survey |
Morning | Intermediate Shell |
Afternoon | Introducing Good Software Development Practices with Python |
Evening | END |
Morning | Data analysis with Python (Part 1) |
Afternoon | Data analysis with Python (Part 2) |
Evening | Post-workshop survey |
END |
To participate in a Data Carpentry workshop, you will need access to software as 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.
If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.
Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:
The setup instructions for the Data Carpentry Ecology workshops (with Python) can be found at the workshop overview site.