DeepLearning.AI Claude Code

学习笔记整理自 DeepLearning.AI 官方课程 "Claude Code: A Highly Agentic Coding Assistant",由 Andrew Ng 和 Anthropic 的 Elie Schoppik 主讲。

• 原始课程: Claude Code: A Highly Agentic Coding Assistant
• 课程平台: DeepLearning.AI Short Courses
• 主讲人: Andrew Ng (吴恩达) & Elie Schoppik (Anthropic)
• 内容性质: 个人学习笔记整理与分享

Master Claude Code, Anthropic's powerful AI coding assistant, through hands-on lessons covering:

• Claude Code Architecture - Understand how Claude Code works under the hood
• Feature Development - Build features efficiently with AI assistance
• Testing & Debugging - Automate testing and resolve errors intelligently
• Advanced Workflows - GitHub integration, parallel development, and MCP servers
• Real-World Projects - RAG chatbots, e-commerce dashboards, and Figma-to-web apps

courses/
├── 00. Overview.md # Learning objectives and course roadmap
├── 01. Introduction.md # Getting started with Claude Code
├── 02. What is Claude Code?.md # Architecture and capabilities
├── 03. Course Notes.md # Resources and references
├── 04. Setup & Codebase Understanding.md
├── 05. Adding Features.md
├── 06. Testing, Error Debugging and Code Refactoring.md
├── 07. Adding Multiple Features Simultaneously.md
├── 08. Exploring Github Integration & Hooks.md
├── 09. Refactoring a Jupyter Notebook & Creating a Dashboard.md
├── 10. Creating Web App based on a Figma Mockup.md
├── 11. Conclusion.md
└── 12. Prompts & Summaries of Lessons.md

Build a full-stack Retrieval-Augmented Generation chatbot with:

• FastAPI backend
• React frontend
• Vector database integration
• Real-time streaming responses

Transform Jupyter notebook analytics into an interactive web dashboard:

• Data visualization
• Performance metrics
• Export functionality
• Responsive design

Convert UI mockups into functional applications:

• Playwright integration
• Automatic component generation
• Responsive implementation
• Production-ready code

• Basic Python and Git knowledge
• Interest in AI-assisted development
• No prior Claude Code experience required

1. Start with the Overview - Read courses/00. Overview.md for learning objectives
2. Follow Sequentially - Lessons build upon each other
3. Practice Along - Apply concepts in your own projects
4. Reference Commands - Use courses/12. Prompts & Summaries of Lessons.md for quick lookup

• English - Primary course content
• 中文 - Chinese translations available (see 吴恩达 x Anthropic:Claude Code 终极教程 01.md)

• Effective prompting strategies
• Project structure understanding
• Parallel feature development
• Automated testing workflows
• GitHub integration patterns
• MCP server extensions

• 原始课程内容版权归 DeepLearning.AI 所有
• 本仓库为个人学习笔记整理,仅供学习交流使用
• 如需官方课程内容,请访问 DeepLearning.AI 课程页面

This is a reference repository for course materials. For course feedback or questions, please contact DeepLearning.AI directly.

Note: This repository contains course transcripts and notes only. For hands-on practice, install Claude Code and follow along with the lessons.