Prompt Engineering for Claude: Context and Tool Use

AI models are only as good as the instructions they receive. To unlock the full potential of Claude, you need to understand how to structure prompts, handle massive amounts of text, and connect the model to external tools. This text-based course takes you from the absolute basics of natural language instructions to the techniques used by modern LLM developers. You will read through practical examples, understand how to structure complex queries, and learn the foundational patterns for integrating AI into real-world workflows. What you will learn: Understand foundational prompt engineering principles and key terminology. Format prompts effectively using XML tags and structured instructions. Manage long context windows for extensive document analysis and summarization. Implement tool use (function calling) to connect Claude to external data sources. Apply basic Retrieval-Augmented Generation (RAG) concepts to improve accuracy and reduce hallucinations. Design robust system prompts for consistent and reliable outputs. The course begins with core definitions and basic prompting mechanics before moving into complex scenarios like multi-step reasoning and tool integration. You will explore carefully written explanations and prompt snippets that you can immediately practice and adapt for your own projects. Designed for beginners, developers, and AI enthusiasts, this course requires no prior programming experience—just a desire to learn how to communicate effectively with AI. Start reading today and build the skills to create powerful, context-aware applications.