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COVID+DS: Key elements of the analytical toolbox for understanding COVID-related data


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The ability to make rapid, data-driven decisions is a key component for prioritizing COVID-19 research, treatment, and public health initiative. This session provides an introduction to the emerging field of data science using the R software language, including data analysis and visualization, with a particular focus on its utility for insights in COVID-19. No prior knowledge of data science or computer programming is assumed; laptops are required. Attendees will be provided with COVID-19 dataset examples, and introduced to R packages and code used to examine data. Particular attention will be paid to code interpretation and data provenance methods by learning to generate reproducible data output files. Although specific datasets will be used for analysis in class, this workshop will provide broadly applicable tools to reproducibly analyze and visualize data across a wide continuum.

This session is part of the Duke+Data Science (+DS) program virtual series on COVID-19 + Data Science.

On the day before the session, all registrants will receive an e-mail with a link and meeting information.


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Status Archived
Date Tuesday, June 30th, 2020
Time 4:00pm - 5:00pm
Location Virtual Classroom
Leader Matthew Hirschey
Enrolled 321