Many graduate programs and research projects require proficiency in coding and working with data. This 2-session intensive workshop is intended to introduce graduate students who have little or no computational background to the open-source Python programming language. This series is organized and instructed by graduate students, with support from the Davis Python Users Group and UC Davis DataLab. This is a great opportunity to learn a new skill and meet other members of the graduate community! Each session will begin with demonstrations on fundamental Python topics, followed by Q&A and open practice where learners can work on challenge assignments together and ask questions to the volunteer instructors. Each challenge assignment builds on the previous sessions, so by the end of the series learners will have a complete Python project for their portfolios. This workshop is open to all UC Davis graduate students and postdoctoral scholars. Attendance at both sessions is required. Instruction is in-person and seats are limited. A Zoom link (e.g., broadcast) will be available for those who are offsite and would like to watch the demonstrations.

After this workshop, learners will be able to:

– Use basic Python programming syntax;

– Use packages such as NumPy and Pandas;

– Use visualization tools;

– Write reusable functions;

– Identify where to go to learn more!

Prerequisites

This introductory series is intended for graduate students and postdoctoral researchers and does not require prior programming experience. Participants will need to bring a laptop on which they can install software and access the UC Davis wireless network (eduroam).

Software

In advance of the first session install the R, RStudio, and Git software onto your laptop. If you are using Windows, you will need to install additional software. Instructions can be found in DataLab's installation guide. Need help with the installation? Register to attend one of our weekly office hours.

Can't make it to this training? Check out upcoming workshop schedule. Recordings of prior workshops are also available in DataLab's training archive.