Introduction to Python - 3-Part Series

Description

Many graduate programs and research projects require proficiency in coding and working with data. This training is designed to expose graduate students who have little to no computational background to the open source Python coding language. This 3-day intensive workshop series (9/6, 9/7, 9/8) by the Davis Python Users Group is hosted by the UC Davis DataLab and is open to all UC Davis graduate students and postdoctoral scholars. Attendance at all three sessions is required. 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. The assignment builds off the previous sessions so by the end of the series learners will have a complete Python project for their portfolios. This training is designed for in-person instruction and seats are limited. A Zoom link will be available for those unable to attend who would like to watch the demonstrations.     

Workshop series dates and time: September 6, September 7, and September 8, 2022, 5:00 PM – 7:00 PM.

Learning Objectives: After this workshop, learners will be familiar with basic Python programming syntax, libraries such as NumPy and Pandas, visualization tools, writing reusable functions, and identifying where to go to learn more.             

Prerequisites:: None      

Software: Python

Instructors: UC Davis graduate students Maggie Berrens, Parker Bremer, Frank Cerasoli          

Instructors’ Biographies

Maggie Berrens is a physical chemistry Ph.D. candidate, working in Davide Donadio’s lab. She received a B.S. from University of Puget Sound in mathematics and chemistry. Her research involves using computational tools to investigate the effect of adsorbed species on the structure and dynamics of ice surface and ice surface's effect photodegradation of pollutants in clouds and snow-pack.

Parker Bremer is an analytical chemistry Ph.D. candidate in Oliver Fiehn's lab. He designs data pipelines and informatics analyses for data from mass spectrometers. He received a B.S. in Chemistry from UC Davis and an M.S. in Physical Chemistry from CSU Long Beach.

Frank Cerasoli is a Postdoc working in Davide Donadio’s lab. He received his Ph.D. in Computational Materials Science, and M.S. in Physics from University of North Texas and a B.S. in Physics from The University of Texas at Austin."