In this course, you will be introduced to the four phases of the disaster management cycle; mitigation, preparation, response, and recovery. You’ll work through two case studies in this course. In the first, you will use computer vision to analyze satellite imagery from Hurricane Harvey in 2017 to identify damage in affected areas. In the second, you will use natural language processing techniques to explore trends in aid requests in the aftermath of the 2010 earthquake in Haiti.
AI and Disaster Management
AI and Disaster Management
This course is part of AI for Good Specialization
Instructor: Robert Monarch
Sponsored by Coursera Learning Team
8,402 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(199 reviews)
Beginner level
Recommended experience
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
3 assignments
Taught in English
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This course is part of the AI for Good Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
What's included
13 videos4 readings1 assignment
What's included
11 videos3 readings1 assignment3 ungraded labs
What's included
12 videos3 readings1 assignment3 ungraded labs
Instructor
Instructor ratings
4.8 (50 ratings)Offered by
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Learner reviews
4.7
199 reviews
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Showing 3 of 199
FF
5
Reviewed on Jul 9, 2023
Great course. Excellent presentation and very motivational
MN
5
Reviewed on Dec 9, 2024
Great lectures, very insighful; I enjoyed the labs, and the structured framework for approaching the projects. The whole specialization is worthwhile!
VH
5
Reviewed on Aug 15, 2023
Great course with very interesting and thought-provoking content. Beginner friendly and excellent code-walkthrough! I can highly recommend the whole 'AI for Good' series.
Recommended if you're interested in Data Science
University of Pittsburgh
Coursera Instructor Network
Yonsei University
The State University of New York
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