Introduction to Generative AI and Multi-Agent Systems

Generative AI is transforming how we build software, automate tasks, and solve complex problems. Understanding how to orchestrate multiple AI agents to work together is the next frontier in technology. This text-based course guides you from the fundamental concepts of Large Language Models (LLMs) to the design of collaborative multi-agent systems. You will learn how to structure prompts, connect models to external data sources, and coordinate multiple specialized agents to solve complex workflows. What you'll learn: * Understand the core architectures of Large Language Models and Generative AI. * Apply modern prompt engineering techniques to guide model behavior effectively. * Explore Retrieval-Augmented Generation (RAG) and integrate vector databases. * Design multi-agent workflows where specialized AI agents collaborate on tasks. * Implement basic conversational patterns and autonomous decision-making loops. * Analyze the safety, ethical considerations, and limitations of modern AI systems. You will start with key terminology and foundational AI concepts before progressing to hands-on structural design for single prompts, RAG systems, and multi-agent environments. Through written explanations and code walkthroughs, you will develop a practical mental model of modern AI orchestration. This course is designed for beginners, developers, and tech enthusiasts who want to understand Generative AI and multi-agent design from the ground up, with no prior AI experience required. Start reading today to master the fundamentals of generative AI and multi-agent architectures.