Explore a compelling data science project focused on predicting global air pollution in the post-COVID era through this insightful 56-minute video from the Alan Turing Institute. Join host Christina as she reunites with former collaborators Prithviraj Pramanik and Dr. Subhabrata Majumdar to discuss their volunteer work with Solve for Good, a platform connecting social good organizations with data scientists. Delve into their collaboration with UNICEF, where they developed a post-pandemic global air pollution model aimed at mapping child exposure to harmful air pollutants. Gain valuable insights into how data science can be leveraged for social good, the challenges of modeling air pollution on a global scale, and the potential impact of such projects on public health and policy-making.
Data Science for Social Good - Predicting Air Pollution in a Post-COVID World
Alan Turing Institute via YouTube
Overview
Syllabus
Data Science for Social Good: Predicting air pollution in a post-COVID world?
Taught by
Alan Turing Institute
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