Software Carpentry: Foundations of Unix, Git and Python
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Software Carpentry: Foundations of Unix, Git and Python
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 for using the command prompt and version control for the Unix shell, plotting and programming in Python, and version control with Git.
Thursday, we will meet from 9-5, with light breakfast, coffee, and lunch provided. Friday, due to graduation, we will start at 10:00, still with breakfast, drinks and lunch provided. We will conclude the primary instruction section at 5:00 but offer additional training or assistance from 5:00-6:00 on Friday for those who are interested.
By the end of the workshop, learners will:
- Manipulate files and data using a Unix shell, Python and Git
- Automate operations on multiple files using a Unix shell
- Familiarize themselves with common data types, programming concepts and procedures in Python
- Practice project management and collaboration in Git
- Identify and resolve errors independently
- Identify options for self-directed and guided learning related to Unix, Python and Git
The workshop is open to anyone. You do not need any programming experience to participate but you will need access to a Windows, Mac or Linux computer. The workshop will be hosted in-person only. Instructions for accessing course material and installing software will be sent in advance. For questions, contact Data Education Coordinator Nathaniel Porter (ndporter@vt.edu).
For more information on our curriculum, visit https://software-carpentry.
If you are an individual with a disability and desire an accommodation, please email library-event-accessibility-g@vt.edu at least 10 business days prior to the event.
- Dates & Times:
- 9:00am - 5:00pm, Thursday, May 12, 2022
10:00am - 5:00pm, Friday, May 13, 2022
- Location:
- Newman 207A
- Campus:
- Blacksburg Campus
- Audience:
- Alumni Beginners Faculty/Staff Graduate Students Public Undergraduates
- Categories:
- Workshop > Data Science Workshop