Generative AI Foundations: Understanding LLMs and Prompt Engineering

Generative artificial intelligence is transforming how we work and build, yet the underlying concepts often seem locked behind complex technical jargon. This course untangles the mystery, guiding you step-by-step through the core terminology and mechanics of modern AI. You will transition from a curious observer to a confident practitioner who understands how large language models function, how data types influence AI outputs, and how to apply foundational prompt engineering techniques to get precise results. What you'll learn: - Understand the core differences between artificial intelligence, machine learning, deep learning, and generative AI - Explore how different data types, including text, images, and code, are processed by generative models - Learn the fundamental mechanics of Large Language Models and how they predict next tokens - Practice basic prompt engineering techniques to guide AI outputs effectively - Discover modern concepts like Retrieval-Augmented Generation and vector databases at a conceptual level - Evaluate the ethical considerations, limitations, and safety guidelines of deploying generative AI solutions You will start by learning key terminology, basic concepts, and foundational definitions before exploring how these models are trained and applied. Through clear written explanations and practical conceptual exercises, you will follow a structured path from basic history to modern, real-world AI applications. This course is designed specifically for beginners with no prior technical background or programming experience. Anyone looking to build a solid conceptual foundation in modern AI will find this course accessible and highly valuable. Start reading today to unlock the potential of generative AI and build your foundational knowledge.