Generative AI: Principles, Prompt Engineering, and RAG

Generative artificial intelligence is transforming how we work, write, and build. Understanding how these models function is no longer optional for tech-forward professionals. This text-based course guides you from the fundamental architectures of Large Language Models (LLMs) to advanced concepts like Retrieval-Augmented Generation (RAG). You will develop a deep conceptual understanding of generative models, enabling you to design effective prompts, leverage vector databases, and integrate AI tools into your daily workflows. What you'll learn: - Understand the foundational mechanics of generative AI, including transformers and neural network basics. - Master prompt engineering techniques to elicit precise, high-quality outputs from language models. - Explore Retrieval-Augmented Generation (RAG) and how vector databases connect LLMs to external data sources. - Analyze the ethical implications, bias, and security considerations of deploying generative AI. - Evaluate different model architectures to choose the right tools for specific business use cases. You will begin by exploring core definitions and foundational concepts before moving into practical prompt design and modern data retrieval patterns. Through clear written explanations and conceptual exercises, you will build a robust framework for working with artificial intelligence. This course is designed for beginners, business professionals, and aspiring developers who want to understand generative AI from the ground up with no prior technical prerequisites. Start reading today to build the skills needed to navigate the future of technology.