Foundations of Generative and Agentic AI

Artificial intelligence is evolving from passive tools that answer questions into active agents that can plan, execute, and automate complex workflows. Understanding how these generative and agentic systems function is essential for anyone looking to stay ahead in the modern digital landscape. This text-based course guides you through the core principles of modern AI, taking you from the basics of large language models to the architecture of autonomous agents. You will gain a clear, conceptual understanding of how these systems think, make decisions, and interact with external tools to solve real-world problems. What you'll learn: - Understand the fundamental mechanics of Large Language Models (LLMs) and how they process information. - Apply core prompt engineering techniques to guide AI models toward accurate and context-aware outputs. - Explore Retrieval-Augmented Generation (RAG) patterns and the role of vector databases in providing external knowledge. - Design basic agentic workflows where AI agents plan, use tools, and collaborate to achieve specific goals. - Evaluate safety, ethics, and best practices for deploying autonomous systems in professional environments. You will start with foundational terminology and the basic mechanics of generative models before gradually moving into complex agent architectures, all explained through clear written concepts and practical code walkthroughs. This course is designed for beginners, professionals, and tech enthusiasts who want to understand the next wave of AI without needing a background in advanced machine learning. Begin reading today to build a strong foundation in the future of autonomous technology.