Spring 2022 Course Descriptions

DS 143-01 Data Science for Sustainability

D. Sunter
T 12:00-2:45a, Anderson Hall 309

Crosslisted as ME 193. This course explores emerging topics in data science and statistical learning with applications to the three pillars of sustainability (environmental, economic, and social). Students learn to build, estimate, and interpret models that describe phenomena in the broad area of energy and environmental decision-making with an emphasis on social justice. Students leave the course as both critical consumers and responsible producers of data-driven analysis. The objectives of this class include i) learning a suite of data-driven modeling and prediction tools, ii) building the programming and computing expertise to use those tools, and iii) developing the ability to formulate an analysis to answer sustainability questions of interest to industry and/or government partners.

Prerequisite: This course uses Python. Prior experience with statistics and programming is required.

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