Introduction to Large Language Models (LLMs)

Large language models are transforming how we interact with technology, yet understanding how they actually process and generate text can seem like a mystery. This text-based course demystifies the core mechanics of generative AI, helping you build a solid conceptual foundation from the ground up. By reading through these structured guides, you will transition from a curious observer to someone who understands how models are trained, how they generate responses, and how modern applications use them to solve real-world problems. You will gain the vocabulary and context needed to discuss, evaluate, and work with artificial intelligence tools effectively. What you'll learn: - Understand the fundamental architecture and training processes of large language models - Explain the difference between pre-training, fine-tuning, and modern alignment techniques - Apply basic prompt engineering principles to guide model outputs effectively - Explore the concepts behind Retrieval-Augmented Generation (RAG) and vector databases - Identify common limitations of language models, including bias and hallucination The course begins with key terminology and foundational definitions before guiding you through the mechanics of text generation, prompt design, and modern application patterns. You will progress through clear, written explanations and practical conceptual exercises at your own pace. This introductory course is designed for absolute beginners, business professionals, and aspiring developers with no prior background in machine learning or programming. Start reading today to build your foundational knowledge of generative AI.