Introduction to Generative AI and Symbolic Reasoning

Modern artificial intelligence is moving beyond simple text generation toward systems that can reason, plan, and verify their outputs. Understanding how to combine the creative power of generative models with the logical precision of symbolic reasoning is the key to building the next generation of intelligent software. This text-only course guides you from absolute beginner to a confident practitioner who understands how large language models and symbolic AI work together. Through clear written explanations, conceptual breakdowns, and practical text-based exercises, you will learn how to design hybrid AI systems that are both creative and logically sound. What you'll learn: Understand the foundational principles of generative AI, transformers, and large language models; Explore the core concepts of symbolic AI and rule-based reasoning systems; Analyze how to integrate generative models with symbolic logic to solve complex reasoning tasks; Apply modern prompt engineering techniques and Retrieval-Augmented Generation patterns; Evaluate the strengths, limitations, and ethical considerations of hybrid AI architectures; Practice designing logical workflows that validate and constrain generative outputs. The course begins with essential terminology and the historical foundations of both neural and symbolic AI. You will then progress through structured modules exploring transformer architectures, logic engines, and modern integration patterns, all illustrated with clear written examples and conceptual walk-throughs. This course is designed specifically for beginners, requiring no prior background in machine learning or advanced mathematics. Start reading today to master the intersection of generative power and logical reasoning.