Foundations of Generative AI and Autonomous AI Agents

Generative AI is shifting from simple chat interfaces to autonomous systems that can reason, plan, and act. If you want to understand how these modern intelligent systems work and how to build them from the ground up, starting with the fundamentals is essential. This text-only course guides you through the core concepts of generative AI before diving into the architecture of autonomous AI agents. You will transition from writing basic prompts to understanding how agents decompose complex tasks, utilize external tools, and maintain memory. What you'll learn: - Understand the core architectures of Large Language Models and foundation models. - Apply advanced prompt engineering techniques to guide model reasoning. - Implement Retrieval-Augmented Generation (RAG) patterns using vector databases. - Design autonomous agent workflows that utilize planning and tool calling. - Configure memory systems to help agents maintain state and context. - Evaluate agent performance and address common challenges. The course begins with foundational definitions and key terminology, ensuring you have a strong grasp of the basics before moving on to step-by-step agent design patterns. This course is designed for beginners, developers, and technology enthusiasts who want a structured introduction to AI agents, with no prior AI experience required. Start reading today to master the next generation of autonomous AI systems.