Artificial Intelligence Foundations: Logic, Search, and Modern Agents

Artificial intelligence is reshaping how we solve complex problems, yet mastering it requires understanding the core algorithms that power these technologies. This course introduces you to the foundational principles of AI, guiding you from classic symbolic logic to modern autonomous systems. You will progress from reading about basic definitions to understanding how intelligent agents make decisions, solve search problems, and optimize outcomes in unpredictable environments. By exploring both classic computer science algorithms and contemporary agentic paradigms, you will gain the conceptual clarity needed to analyze and design smart systems. What you'll learn: - Understand the foundational terminology of artificial intelligence, logic systems, and knowledge representation. - Apply classical search algorithms and optimization techniques to solve complex pathfinding and planning problems. - Design autonomous agents capable of reasoning, making decisions, and adapting to dynamic environments. - Explore modern agentic workflows, including basic retrieval-augmented generation patterns and prompt-based reasoning. - Analyze how game-playing algorithms and adversarial search are used in strategic decision-making. The course begins with essential terminology and the history of symbolic AI, before moving into search heuristics, logic programming, and modern agent architectures. You will learn entirely through clear written explanations, structured conceptual breakdowns, and practical code snippets. This course is designed for beginners, developers, and tech enthusiasts looking for a rigorous, text-based introduction to AI concepts without needing advanced mathematics or prior machine learning experience. Start your journey into the world of artificial intelligence and learn to think like an AI engineer today.