This class is no longer accepting registrations
Region 5 is excited to announce we will be hosting two free online sessions of Library Carpentry in Winter and Spring of 2022. Both sessions have 25 spots available.
The Spring session will be April 26-28, 12:30pm-5:30pm PDT and covers the same material as the Winter session, so choose the date that works best for you. Spring registration will close Tuesday, April 19th at 6 p.m. PDT. Notification of your registration approval and the Zoom link will be provided by Friday, April 22nd, noon PDT.
Library Carpentry focuses on building software and data skills within library and information-related communities. Their hands-on, approachable workshops empower people in a variety of roles to use software and data in their own work and support effective, efficient, reproducible practices. Learn more about Library Carpentry on their website.
The Library Carpentry workshop is broken into four lessons: Workshop Overview, Introduction to Working with Data (Regular Expressions), The UNIX Shell, Open Refine, and Introduction to Git. You can learn more about the lessons on their website.
The Library Carpentry workshops are open to all, and the training will focus on skills for library workers. We encourage anyone interested in Library Carpentry skills to register, no prior knowledge is needed. We will prioritize registration from Region 5 states (Alaska, California, Hawaii, Nevada, Oregon, Washington, and U.S. Territories and Freely Associated States); however, if we are not able to fill all 25 spots with Region 5 participants we will be accepting non-Region 5 registrants on a first come first serve basis.
Any questions about the Library Carpentry workshops can be directed to email@example.com
- Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks;
- Identify and use best practices in data structures;
- Learn how to programmatically transform and map data from one form to another;
- Work effectively with researchers, IT, and systems colleagues;
- Automate repetitive, error prone tasks.