The best way to learn how to program is to do something useful, so this introduction to Python is built around a common scientific task: data analysis. This is an introduction to the basics of writing a program to process and analyze data -- learners will learn to get started with a Jupyter notebook, input and output (including reading and writing files), basic programming concepts (variables, loops, conditionals), processing and manipulating data, and plotting.

IMPORTANT: This workshop is two sessions: 10/8/21 and 10/15/21. Registration and attendance at the first session is a prerequisite for the second.

General Information

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: Online via Zoom

When: Friday October 8 and Friday October 15, 2021. 1:00 p.m. - 5:00 p.m.

Requirements: Participants must bring a laptop 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 (please see the "Python" setup instructions listed here).

Materials will be provided in advance of the workshop. If we can help making learning easier for you (e.g. sign-language interpreters, additional accommodations) please get in touch (using contact details below) and we will attempt to provide them.

Workshop organization note: A full Software Carpentry workshop typically consists of two days of in-person instruction, covering the Unix shell (half day), version control with Git (half day), and a full day of either Python or R. For online workshops, we have separated this curriculum into a series of shorter sessions. For the full workshop curriculum, please see our upcoming event calendar to register for Shell and Git lessons.