AI for Climate Change
Offered By: DeepLearning.AI via Coursera
Course Description
Overview
In Course 2: AI for Climate Change, you will begin by learning the basics of anthropogenic climate change — why it is happening, its projected impacts, and how it is already driving extreme weather around the globe. You will then learn how machine learning techniques can lessen climate change’s impacts and help communities prepare for those that do occur.
Learners will take part in two hands-on labs. In the first, you will use data modeling techniques to visualize how climate change is modeled to cause average temperatures to change in different locations around the world. In the second, you will build a model that forecasts how much power wind turbines in different locations will generate.
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 be familiar with high school-level mathematics and basic spreadsheet operations. It is recommended that learners first complete Course 1: AI for Good.
Learners will take part in two hands-on labs. In the first, you will use data modeling techniques to visualize how climate change is modeled to cause average temperatures to change in different locations around the world. In the second, you will build a model that forecasts how much power wind turbines in different locations will generate.
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 be familiar with high school-level mathematics and basic spreadsheet operations. It is recommended that learners first complete Course 1: AI for Good.
Taught by
Robert Monarch
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent