Foundational AI: Logic, Optimization, and Building Intelligent Systems

Artificial intelligence is transforming every industry, yet its core mechanisms—how computers reason, learn, and make decisions—often remain a mystery. This course breaks down those complex ideas into accessible, written explanations. By the end of this course, you will have a solid theoretical understanding of AI fundamentals, allowing you to interpret intelligent systems and apply foundational algorithms to problem-solving scenarios. What you'll learn: * Understand the core concepts of Artificial Intelligence, including agents, environments, and rational decision-making. * Master essential search algorithms, such as Breadth-First Search, Depth-First Search, and informed search techniques like A*. * Apply principles of knowledge representation and formal logic to enable computers to reason about the world. * Learn the basics of probabilistic modeling and Bayesian networks for handling uncertainty. * Practice optimization techniques, including local search methods, to find the best solutions in vast problem spaces. * Configure simple machine learning models to classify data and recognize patterns. This course begins with foundational definitions and logic, progresses through classical search and optimization methods, and concludes with an introduction to modern probabilistic and learning models. It is designed for absolute beginners and requires no prior knowledge of programming or advanced mathematics. Start your journey into the world of intelligent systems today.