Practical AI for Social Impact

Overview

Gain a foundational understanding of key AI algorithms and build valuable skills highly sought after in tech and social impact fields. "Practical AI for Social Impact" introduces you to algorithms, including machine learning and reinforcement learning, with additional topics and resources referenced throughout the course. Crucially, this course also addresses special challenges in implementing AI for social impact. Throughout the course, we’ll discuss how to navigate data scarcity, bias, and ethical deployment in real-world communities. Case studies will explore potential scenarios with sequential, adaptive decisions, helping you approach new situations with tact and knowledge. By the end of the course, you’ll have developed skills highly sought after in tech and nonprofit sectors, empowering you to optimize resource distribution and drive systemic change at scale. This is the second course in the three-course series, "Realizing AI for Social Impact", where you will explore use cases and frameworks for deploying AI to achieve social impact.

Syllabus

Modeling the Real World

In this module, you will learn about different kinds of real-world scenarios that might arise and how we have to model them in order to apply AI.

Making Predictions and Decisions

You will explore the fundamentals of machine learning as they relate to AI for social impact. Building on this foundation, you will expand your AI toolbox to address scenarios where decisions must be made continuously, not just once. These concepts will be introduced through relatable case studies designed that you might relate to.