Climate Intelligence 101: accelerating the fight against climate change by making it data-driven Winter 2023

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In recent years a novel approach to the fight against climate change has emerged, fueled by new dramatically more detailed, up-to-date data about the exact sources of greenhouse gas emissions. Sometimes known as “climate intelligence”, this new field focuses on applying data-driven optimization to these newly detailed emissions data sets. Like business intelligence, the goal of climate intelligence is to use data to multiply the impact of new policies, business strategies, and technologies. To reduce more emissions, faster. This course will begin by introducing students to this rapidly emerging new world at the intersection of climate change, data science, economics, and business. But participants should not expect a relaxed, casual winter study. This high-octane course will move fast and remain laser-focused on not merely understanding climate change, but on actually helping fix it. The course will be team taught by an interdisciplinary group of Williams alums and will cover: * A background on emerging new emissions datasets; * How to use big data to rapidly prototype and iterate on testable scientific hypotheses on better ways to reduce emissions; * A lab section in which students will use novel data to develop proposed new concrete, real-world laws, regulations, businesses, NGOs, or inventions; and * How to develop business plans or regulatory proposals to actually make your ideas happen in the real world. It is anticipated, though certainly not required, that after completion of this course many students will literally found the company or help pass the policy in their proposal. Time: about 14 h/wk. (Estimated 3h lecture, 3h lab/practicum, 8h project work).
The Class: Format: lecture
Limit: 30
Expected: NA
Class#: 1139
Grading: pass/fail only
Requirements/Evaluation: Short paper and final project or presentation
Prerequisites: None. But this course will involve manipulating a lot of data! Any of: multivar calculus, stats, econ, ability to code, and/or an entrepreneurial spirit helpful but not required. Please don't take this course if not at least already familiar with Excel.
Enrollment Preferences: If overenrolled, priority should be to students who have passed at least one computer science or econometrics course.
Unit Notes: Gavin McCormick is founder of environmental tech nonprofit WattTime and cofounder of Climate TRACE, a coalition using AI and satellites to measure all Earth's GHG emissions. He's an Eph and has an MS in environmental econometrics from UC Berkeley.
Attributes: EXPE Experiential Education Courses
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