Foundations of Large Language Models: How LLMs Work

Large Language Models (LLMs) are reshaping technology, but understanding how they actually work behind the scenes can feel overwhelming. This course demystifies the core concepts, architectures, and capabilities of these powerful AI systems. You will transition from a curious observer to someone who understands the mechanics of generative AI, enabling you to speak intelligently about AI capabilities and apply foundational concepts to modern business and technical problems. What you'll learn: - Understand the foundational transition from traditional machine learning to modern transformer-based architectures. - Explain how LLMs are trained, including pre-training, fine-tuning, and alignment. - Analyze core capabilities, including in-context learning, reasoning, and text generation. - Explore modern patterns like Retrieval-Augmented Generation (RAG) and basic prompt engineering. - Evaluate the limitations, ethical challenges, and safety considerations of deploying models. The curriculum begins with essential AI terminology and foundational definitions before guiding you through model training processes, modern architectural patterns, and practical deployment considerations. Designed specifically for beginners, this text-only course requires no prior programming or advanced mathematics background. Start reading today to unlock the potential of modern generative AI.