Generative AI and Multi-Agent Systems Fundamentals

The field of artificial intelligence is moving beyond simple chatbots toward complex systems where multiple AI entities work together to solve problems. Understanding how to orchestrate these collaborative systems is becoming a vital skill for anyone looking to work in the modern tech landscape. This course provides a clear path from basic concepts to the architecture of autonomous agents. You will transform your understanding of AI from a single-response tool into a sophisticated framework of interconnected agents capable of handling automated workflows. By focusing on the logic and structure of these systems, you will gain the knowledge needed to build more reliable and capable AI applications. What you'll learn: - Understand the core architecture of Large Language Models and how they process text-based data. - Master prompt engineering techniques to refine AI outputs for specific professional use cases. - Explore Retrieval-Augmented Generation (RAG) patterns to connect models with external knowledge bases. - Design multi-agent architectures where specialized AI entities collaborate on complex goals. - Implement memory and state management to maintain context across long-running AI tasks. - Apply safety guardrails and ethical considerations to ensure responsible AI deployment. The course begins with essential terminology and foundational definitions before progressing into the mechanics of model orchestration and agent communication. It is designed for beginners and curious professionals who want to understand the next generation of AI technology without requiring a background in data science. Start building your understanding of collaborative AI systems today.