This course provides a broad introduction to artificial intelligence as a collection of methods for building systems that perceive, learn, reason, and act in the world. Participants will learn how AI systems are designed and evaluated in practice, from predictive models and recommendation systems to generative AI and agentic systems. Alongside core technical concepts in machine learning and deep learning, the course emphasizes how AI is deployed in real-world settings, while emphasizing the crucial importance of bias assessment and the principles of responsible AI. Throughout, the focus is on developing intuition for how modern AI systems work, where they succeed and fail, and how they should be responsibly integrated into high-stakes environments.
This course is designed for students interested in understanding the principles behind modern AI systems and their applications, with an emphasis on conceptual understanding, critical evaluation, and real-world impact rather than specific implementation details.
