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In Course 3, AI for Disaster Response, you will begin by learning how natural disasters create both short and long-term impacts on the economy, environment, and community. You will then learn how to mitigate some impacts using a framework for planning, designing, and implementing AI for Good projects.
You will get hands-on experience through a pair of case studies. The first focuses on the catastrophic 2010 earthquake in Haiti. You will use natural language processing (NLP) to compare requests for aid that victims made shortly after the earthquake with those that they made several months later. The second case study looks at Hurricane Harvey, which devastated parts of the Caribbean, Mexico, and the southern United States in 2017. You will use computer vision to identify hurricane damage from satellite imagery.
This course is part of the AI for Good Specialization, which demonstrates how AI is being harnessed to tackle some of the world’s biggest challenges — and provides a framework for you to be part of the solution.
This is a beginner-friendly course. Learners should know high school-level math and basic spreadsheet operations. It is recommended that learners first complete Course 1 and Course 2.
You will get hands-on experience through a pair of case studies. The first focuses on the catastrophic 2010 earthquake in Haiti. You will use natural language processing (NLP) to compare requests for aid that victims made shortly after the earthquake with those that they made several months later. The second case study looks at Hurricane Harvey, which devastated parts of the Caribbean, Mexico, and the southern United States in 2017. You will use computer vision to identify hurricane damage from satellite imagery.
This course is part of the AI for Good Specialization, which demonstrates how AI is being harnessed to tackle some of the world’s biggest challenges — and provides a framework for you to be part of the solution.
This is a beginner-friendly course. Learners should know high school-level math and basic spreadsheet operations. It is recommended that learners first complete Course 1 and Course 2.
