Sept. 15, 29-30: Oct. 27: Nov. 10-11: Dec. 8.
9:00 am - 12:30 pm
Instructors: Trisha Adamus, Christina Koch, Casey Schacher, Sarah Stevens, Chris Endemann
Helpers: Christopher Endemann, Erwin Lares, Clare Michaud, Benjamin Ortiz, Jean-Yves Sgro, Sarah Stevens
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Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. 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 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: Sept. 15, 29-30: Oct. 27: Nov. 10-11: Dec. 8. . 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. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you.
Contact: Please email firstname.lastname@example.org 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.
|September 15th||Data Science for Clinicians and Docs||NA||Etherpad|
|September 29-30th||Intro to Docker||For this workshop, you need to be familiar with all of the commands taught in this Unix Shell lesson||Etherpad|
|October 27th||Git/Github||For this workshop, you need to be familiar with all of the commands taught in this Unix Shell lesson||Etherpad|
|November 10-11th||Intro to Machine Learning with sklearn||For this workshop, you need to have a base familiarity with python||Etherpad|
|December 8th||Interactive Data Visualizations in Python||For this workshop, you need to have a base familiarity with python, the unix shell, and github.||Etherpad|
The lesson taught in this workshop is being piloted and a precise schedule is yet to be established. The workshop will include regular breaks. If you would like to know the timing of these breaks in advance, please contact the workshop organisers. For a list of lesson sections and estimated timings, visit the lesson homepage.
To participate in a 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:
|Date||Workshop||Set Up Items|
|September 15th||Data Science for Clinicians and Docs||Set Up Instructions here|
|September 29-30th||Intro to Docker||Set Up Instructions here|
|October 27th||Git/Github||Set Up Instructions here|
|November 10-11th||Intro to Machine Learning with sklearn||Set Up Instructions here|