In this module, you'll learn systematic approaches to creating and testing effective prompts for Claude. You'll start by building evaluation pipelines that let you test prompts objectively using automated grading methods. You'll learn to generate comprehensive test datasets that expose both strengths and weaknesses in your prompts.

In this module, you'll explore Claude's advanced features and learn to build applications where Claude can call functions and interact with external systems. You'll start with features like extended thinking for complex reasoning, image and PDF support for multimodal applications, and prompt caching to reduce latency and costs.

In this module, you'll learn the Model Context Protocol, a standardized way to build servers and clients that provide tools and resources to Claude applications. MCP lets you create reusable integrations that work across different applications instead of building custom tool implementations for each project.

In this module, you'll learn to build retrieval augmented generation systems that provide Claude with relevant information from your documents and data. RAG addresses Claude's context limits by retrieving only the relevant portions of large document collections based on user queries.

In this module, you'll learn to use Claude Code for development tasks and build applications using Computer Use for automated interface interactions. Claude Code accelerates development by helping with code generation, refactoring, debugging, and documentation tasks.

In this module, you'll learn to design and implement agentic workflows that handle complex, multi-step tasks. You'll start by understanding when to use workflows versus simple prompts, then learn three core workflow patterns: parallelization for executing multiple tasks simultaneously, chaining for sequential processing where outputs feed into subsequent steps, and routing for conditional branching based on intermediate results.