Foundations of Large Language Models and Prompt Engineering

Large Language Models (LLMs) are reshaping how we interact with technology, but understanding how they function is key to unlocking their potential. This course demystifies the core concepts behind generative AI and natural language processing. You will transition from a curious beginner to a confident practitioner who understands how LLMs process text, how to structure effective prompts, and how modern generative AI architectures are built. What you'll learn: Understand the foundational architecture, terminology, and capabilities of Large Language Models; Apply prompt engineering techniques to guide model outputs and improve accuracy; Explore the role of vector databases and Retrieval-Augmented Generation (RAG) in modern AI systems; Identify key use cases and ethical considerations for deploying language models in real-world scenarios; Analyze how developers leverage APIs and orchestration frameworks to build intelligent text applications. The course begins with essential definitions and foundational AI concepts before guiding you through practical prompting strategies and modern system architectures. You will learn through clear written explanations, structured examples, and conceptual exercises. Designed for absolute beginners, technology enthusiasts, and professionals looking to understand the fundamentals of LLMs, this course requires no prior programming experience or advanced mathematics. Start reading today to build a solid foundation in the future of artificial intelligence.