Foundations of Generative AI and Intelligent Agents

Generative artificial intelligence is transforming how we work, build, and solve problems, but understanding how these systems actually operate is the first step to leveraging their potential. This written course guides you through the core mechanisms of large language models and the emerging paradigm of autonomous AI agents. By the end of this course, you will transition from a curious observer to a knowledgeable practitioner capable of explaining generative AI architectures, writing structured prompts, and designing basic agentic workflows. You will learn to: 1. Understand the fundamental concepts of generative AI, neural networks, and how large language models process text. 2. Apply foundational prompt engineering techniques to guide model outputs effectively. 3. Explore Retrieval-Augmented Generation (RAG) patterns and how external data sources improve AI accuracy. 4. Design autonomous AI agent architectures that utilize tools, memory, and planning to execute multi-step tasks. 5. Analyze ethical considerations, bias, and security best practices in modern AI deployment. The course begins with essential terminology and foundational definitions before moving into practical prompt design, modern retrieval patterns, and the architecture of multi-agent systems. You will learn entirely through clear written explanations, conceptual breakdowns, and step-by-step text walkthroughs. This course is designed for absolute beginners, professionals, and product managers who want a solid, conceptual foundation in modern AI without needing prior programming experience. Start your journey into the future of intelligent systems today.