Class Central Tips
The AI for Good course is designed to introduce learners to the concept of using artificial intelligence to address social and environmental issues.
We'll start by defining AI for Good, and explore various examples of AI for Good projects. You will get hands-on with a real-world concern, air quality in Bogotá, and use the AI for Good framework to define the problem, identify stakeholders, and determine where AI could fit. You will also learn how to interpret exploratory data analysis (EDA) graphs and use Python to explore air-quality data. The course also covers approaches for missing data imputation, model performance evaluation using mean absolute error (MAE), and interpreting EDA graphs and heatmaps.
This is the first course in the AI for Good Specialization, which demonstrates how AI is being utilized to address 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.
We'll start by defining AI for Good, and explore various examples of AI for Good projects. You will get hands-on with a real-world concern, air quality in Bogotá, and use the AI for Good framework to define the problem, identify stakeholders, and determine where AI could fit. You will also learn how to interpret exploratory data analysis (EDA) graphs and use Python to explore air-quality data. The course also covers approaches for missing data imputation, model performance evaluation using mean absolute error (MAE), and interpreting EDA graphs and heatmaps.
This is the first course in the AI for Good Specialization, which demonstrates how AI is being utilized to address 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.
