Foundations of Artificial Intelligence: Logic, Planning, and Machine Learning

Artificial intelligence is built on a rich foundation of mathematical logic, probabilistic reasoning, and structured planning. Understanding these core concepts is essential for anyone looking to build or work with modern intelligent systems. This text-based course guides you from the absolute basics of symbolic AI to modern machine learning fundamentals, giving you a clear conceptual framework for how AI systems make decisions. What you'll learn: Understand first-order logic and how machines represent and infer knowledge; Explore deterministic and decision-theoretic planning techniques for autonomous agents; Learn the fundamentals of Bayesian networks and probabilistic reasoning under uncertainty; Apply basic supervised learning methods to train predictive models; Discover modern AI concepts including vector databases and prompt engineering fundamentals. The course starts with essential terminology and the philosophical roots of symbolic AI before progressing through logical representation, decision-making algorithms, and probabilistic models. Designed for beginners with no prior AI experience, this course requires no advanced prerequisites. Begin your journey into the mechanics of artificial intelligence today.