Prompt Engineering and Context Grounding for AI Systems

As generative AI becomes a core part of modern software, the ability to guide models reliably is no longer a matter of trial and error—it is a precise engineering discipline. Many developers struggle with unpredictable model outputs because they treat prompts as temporary inputs rather than structured system components.\n\nThis written course transforms how you interact with Large Language Models (LLMs) by teaching you how to design disciplined, repeatable, and secure prompts. You will start with foundational terminology and basic concepts of natural language processing before moving into structured context management, grounding strategies, and safety protocols to ensure your AI applications remain stable and trustworthy in production environments.\n\nWhat you'll learn:\n- Understand the core principles of prompt design, model parameters, and context windows.\n- Apply advanced prompting patterns including few-shot learning, chain-of-thought reasoning, and structured schema outputs.\n- Implement context grounding and Retrieval-Augmented Generation (RAG) basics to prevent model hallucinations.\n- Manage large context windows efficiently while maintaining high retrieval accuracy.\n- Protect your AI systems against security vulnerabilities such as prompt injection and data leaks.\n- Evaluate and monitor prompt performance systematically to ensure consistent outputs over time.\n\nThe course flows systematically from basic definitions and tokenization concepts to advanced schema-based outputs, grounding techniques, and production safety strategies. Through clear written explanations and structured text-based exercises, you will build a robust framework for managing AI behavior.\n\nThis course is designed for beginner developers, technical product managers, and AI enthusiasts who want to move beyond basic chat prompts and learn structured AI orchestration. No advanced programming experience is required.\n\nStart reading today to master the art and science of structured prompt engineering.