Fundamentals of Prompt Engineering and Generative AI

Generative AI is transforming how we work, but getting the best results from Large Language Models (LLMs) requires knowing exactly how to communicate with them. This text-based course teaches you the foundational principles of prompt engineering so you can unlock the full potential of modern AI. By reading through this course, you will transition from writing simple questions to crafting precise, context-rich prompts that guide LLMs to produce accurate, high-quality, and useful outputs. You will understand how these models process language under the hood and how to structure your text to get consistent results. What you'll learn: Understand the fundamental mechanics of Large Language Models and how generative AI processes text; Apply core prompt engineering techniques, including few-shot prompting and chain-of-thought reasoning; Design system prompts to establish clear roles, constraints, and professional tones for AI outputs; Configure context windows and manage token limits effectively to keep conversations coherent; Identify and mitigate common AI limitations, such as hallucinations and biased responses; Explore modern patterns like Retrieval-Augmented Generation (RAG) and how external data enhances prompts. This course starts with essential terminology, explaining how LLMs are trained and how they interpret inputs. From there, you will progress through practical written explanations and step-by-step examples that demonstrate how to structure instructions, manage context, and refine prompts for real-world scenarios. Designed entirely for beginners, this course requires no programming experience or prior background in artificial intelligence. Start reading today to build your foundation in generative AI.