Lessons Learned: Using Python and Jupyter Notebook to Teach Undergraduate Climate Data Analysis

We are currently purchasing and configuring a Juptyer Notebook/Python Server for use across our Climate and Atmospheric Sciences curricula.  We will use Jupyter Notebook (nee iPython) as a tool for teaching data analysis and recording methodologies (e.g., digital lab notebooks) using Python. With instructor feedback, students can learn to add descriptions and discussions inline with code and plots in their notebooks. Additionally, having all student projects on a single server, with a single coding environment, will facilitate feedback and assistance (e.g., finding bugs) from peers and instructors. Students can easily share scripts and notebooks with each other to see various methodologies, or to compare the results of using different data sets (e.g., different CMIP models) in an analysis. In Fall 2016, Climate Data Analysis, ATS 301, will be the first class taught using this new server. This presentation will provide examples of student projects and assignments and highlight lessons from this first implementation: challenges we faced, what worked well, and what didn't.