Prescriptive AI

Introduction to Prescriptive AI

Understand the motivation and opportunities for prescriptive AI, focusing on how this technology can recommend actions to achieve specific outcomes.

Reinforcement Learning Fundamentals

Learn about reinforcement learning, where agents adapt their behavior through trial and error in order to achieve goals in dynamic environments. Uncover the basics of dynamic programming, value-function learning and policy gradient methods, on-policy and off-policy learning, and model-based and model-free methods.

Evolutionary Computation and Optimization

Learn about population-based search algorithms, emphasizing their ability to scale to vast, high-dimensional, and deceptive search spaces to discover surprising and creative solutions.

Mastering Multiobjective Optimization

Learn how to handle problems involving multiple objectives that need to be optimized simultaneously by using techniques for identifying optimal trade-offs between competing objectives.

Surrogate Modeling Techniques

Uncover the techniques of surrogate modeling that allow scaling up the search for prescriptive solutions by several orders of magnitude in complex and costly optimization environments.

Applications in Decision Making, Robotics, and Virtual Agents

Explore how reinforcement learning, evolutionary computation, and conventional optimization techniques can guide strategic planning, resource allocation, and problem-solving. Learn about integrating AI techniques into designing effective control and autonomous behaviors for robots and other virtual agents.

Explainability, Transparency, and Causality

There is a critical need for AI systems to be understandable and transparent to humans. This topic explores approaches to demystifying black-box models and introduces the importance of discerning causal relationships over correlations, leading to more interpretable, reliable, and fair AI decisions.

Responsible AI Deployment

Learn about the best practices for deploying and maintaining AI systems responsibly, including their impact on jobs, the environment, and society. This part of the course will guide you through considerations of training, equitable access, and security.