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Digital Water: Emerging Data Science and Research Software
Course Number: CEE 599 B,D
Christina Bandaragoda, University of Washington
Learn how to use digital infrastructure to publish, manage, and operate software to translate your research between science
domains for research, policy development, and decision-making using observations and models. Discover data, generate and
test hypotheses, and ethically cooperate on reproducible research with online platforms, modeling frameworks, and open
source software for interactive science focusing on water data and translation tools.
Prerequisites: None. Additional resources will be provided for those not familiar with Python. Students new to programming
should anticipate extra time for completing assignments.
1. Make a folder with your name on it for your work; this will be private until consent forms are finished.
2. Upload a Notebook draft and materials for 5 minute presentation OR readme with links to Github.
|The content of this resource can be executed by
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
|JupyterAdmin Tony Castronova
|Tulane University;Louisiana Coastal Protection & Restoration Authority
|Indiana University at Bloomington;O'Neill School of Public and Environmental Affairs;Winona State University;CUAHSI
|Kent State University
|University of Washington
|University of Nevada Reno
|Indiana University at Bloomington
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/