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Robert Monarch

The AI for Good Specialization showcases how AI can be part of the solution when it comes to addressing some of the world’s biggest challenges in areas like public health, climate change, and disaster management.

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The AI for Good Specialization showcases how AI can be part of the solution when it comes to addressing some of the world’s biggest challenges in areas like public health, climate change, and disaster management.

In these courses, you’ll learn from instructor Robert Monarch, who has over 20 years of experience building AI products in industry and working at the intersection of AI and public health and disaster management. Robert is also the author of Human-in-the-Loop Machine Learning, a book focused on human-centered AI applications.

Throughout the courses, you'll hear from experts working on AI for Good initiatives aimed at addressing social and environmental issues. By combining human and machine intelligence, real-world datasets, best practices around data privacy, and ethical considerations, you’ll develop the knowledge and fundamental skills to tackle your own AI for good projects.

These courses were built in partnership with researchers at the Microsoft AI for Good Lab who offered their subject matter expertise throughout the development of the program. We are also grateful to Sasha Luccioni, Climate Lead and Researcher at HuggingFace for her help in forming the high-level program structure, outlining what kinds of topics and case studies would work best for these courses, and recruiting many of the experts that either appear in guest speaker videos or have contributed behind the scenes.

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What's inside

Three courses

AI and Public Health

In this course, you will learn the basics of AI and machine learning and how they are used in real-world AI for Good applications. You will also learn a framework for solving problems with AI. The course ends with a case study featuring three Jupyter notebook labs where you will create an air quality monitoring application for Bogotá, Colombia.

AI and Climate Change

In this course, you'll review the mechanisms behind anthropogenic climate change and its impact on global temperatures and weather patterns. You will work through two case studies, one using time series analysis for wind power forecasting and another using computer vision for biodiversity monitoring. Both case studies are examples of where AI techniques can be part of the solution when it comes to the mitigation of and adaptation to climate change.

AI and Disaster Management

This course introduces the four phases of disaster management: mitigation, preparation, response, and recovery. You'll analyze satellite imagery and explore aid request trends using AI techniques.

Learning objectives

  • Master a step-by-step framework for the development of ai projects.
  • Explore real-world case studies related to public health, climate change, and disaster management.
  • Analyze data and build ai models for projects focused on air quality, wind energy, biodiversity monitoring, and disaster management.

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