Foundations in Artificial Intelligence.

Catalog description

This course provides a comprehensive introduction to the foundations of artificial intelligence. Students will explore a range of topics including search algorithms, constraint satisfaction, and optimization problems, as well as logic and reasoning. The course will introduce probabilistic reasoning, decision theory, and Markov decision processes as frameworks for decision-making under uncertainty. In addition, students will learn the fundamentals of machine learning and examine key issues in trustworthy AI, focusing on fairness, interpretability, and ethical considerations. This course emphasizes both theoretical understanding and practical applications, preparing students to analyze and design AI systems in a variety of domains.