Claude Code in Action

anonymous November 29, 2025

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This course provides comprehensive training on using Claude Code for software development tasks, covering the underlying architecture of AI coding assistants, practical implementation techniques, and advanced integration strategies. You'll learn about Claude Code's context management approaches, and how to extend functionality through MCP servers and GitHub integration. What you'll learn Understand coding assistant architecture: Learn how AI assistants interact with codebases through tool integration and the technical foundations that enable code analysis and modification Explore Claude Code's tool use system: Discover how to leverage multiple tools in combination to handle complex, multi-step programming tasks across various development scenarios Master context management techniques: Learn strategies for maintaining relevant context throughout conversations and effectively referencing project resources for optimal AI assistance Implement visual communication workflows: Understand how to use visual inputs to communicate interface changes and leverage advanced planning features for complex codebase modifications Create custom automation: Explore how to build reusable custom commands and automations that streamline repetitive development tasks Extend functionality with MCP servers: Learn to integrate external tools and services for enhanced capabilities like browser automation and specialized development workflows Integrate with GitHub workflows: Understand how to set up automated code review processes and integrate AI assistance into your existing version control workflows Apply thinking and planning modes: Learn when and how to use different reasoning approaches for various complexity levels of programming challenges Prerequisites Familiarity with command-line interfaces and terminal operations Basic understanding of version control with Git Who this course is for Software developers looking to integrate AI assistance into their coding workflows Teams seeking to implement AI-powered GitHub integration for multiple workflows

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Claude with Google Cloud's Vertex AI

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anonymous

Claude with Amazon Bedrock

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Learn the best practices for agentic coding with Claude Code in this new short course, Claude Code: A Highly Agentic Coding Assistant, built in partnership with Anthropic, and taught by Elie Schoppik, Head of Technical Education. AI coding assistants have evolved rapidly, from tools that help with occasional coding questions and code completion to tools that can autonomously generate code. Claude Code pushed the degree of autonomy by acting as a highly agentic assistant that can plan, execute, and improve code with minimal human input, for more than a few minutes. You and your teammates can now run multiple instances of Claude code and work in parallel on different parts of the codebase. However, coordinating all this involves a set of best practices that can significantly boost your productivity. In this course, you’ll learn best practices for using Claude Code to improve your coding workflow. You’ll learn key tips on how to provide Claude Code with clear context, such as specifying the relevant files, clearly defining the features and functionality, and connecting Claude Code to MCP servers. You’ll apply these best practices to three examples: exploring a RAG chatbot codebase, analyzing ecommerce data in a Jupyter notebook, and creating a web app based on a Figma mockup. In detail, using Claude Code, you’ll: Understand the underlying architecture of Claude Code, the tools it uses to navigate your codebase, and how it stores memory across sessions. Explore and understand the codebase of a RAG chatbot and how information flows between the frontend and the backend. Initiate a CLAUDE.md file inside your project directory containing information and guidelines about your codebase that Claude Code can remember across sessions. Get context into Claude Code by mentioning the relevant files and providing screenshots or images, and control the context using escape, clear, and compact commands. Add features to the frontend and backend of the RAG chatbot: ask Claude Code to plan first to improve its performance, use thinking mode for harder tasks, and brainstorm ideas using Claude Code’s subagents. Write tests to evaluate the RAG chatbot functionalities, and refactor parts of the chatbot. Use git worktrees to run multiple Claude sessions simultaneously, each focused on adding an independent feature to the chatbot. Fix Github issues, and create, review and merge Github pull requests using Claude Code’s Github integration. Execute code before and after using tools through Claude Code hooks. Refactor a Jupyter notebook for e-commerce data analysis and transform it into a dashboard. Connect Claude to the Figma MCP server to import a design mockup to Claude Code, and develop a web interface showing economic data from the Federal Reserve Economic Data. Use Playwright MCP server to automatically open a web browser, take screenshots, and guide Claude Code to improve the UI design of an application. By the end of this course, you’ll have a set of best practices you can apply to speed up and improve your coding workflow.

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