What you'll learn:
- Claude Code Proficiency
- Multi-agent system workflows for complex coding projects
- Strategies for AI-assisted debugging and refactoring
- Confidence to transform your entire development process
- Context Engineering
- Agentic Coding
This course contains the use of artificial intelligence :)
Welcome to the Beta for the Claude Code Crash Course!
This course is currently in Beta and is actively being developed. New, in-depth videos and hands-on projects are added weekly as we build towards a comprehensive 6+ hour curriculum. By enrolling now, you get early access to become a Claude Code power user and the opportunity to provide feedback that shapes the final version of the course!
Please note: This is an advanced course and is not suitable for beginners. This curriculum is designed for professionals and assumes you have a solid background in software engineering and are proficient in Python, Next JS and generative ai. We will be working extensively in the terminal and using the Cursor IDE for seamless integration, but you can follow along with any editor that supports the Claude Code extension.
This course is for software developers, AI engineers, and data scientists who want to move beyond simple chat interactions and harness the full power of Claude Code to build automated, context-aware, and secure development workflows.
What You Will Learn in Claude Code
Claude Code is more than just a coding assistant; it's a powerful, extensible platform for creating AI-driven development tools. This course will teach you to master its core architecture, from basic commands to building complex, multi-agent systems.
Architecture and Core Concepts
Slash Commands: Go beyond basic prompting and learn to control every aspect of Claude Code's behavior, context, and configuration directly from your terminal.
Persistent Memory (CLAUDE .md): Learn to give Claude a long-term memory. We'll cover how to create and manage user, project, and local memory files to store preferences, coding standards, and architectural context that persists across sessions.
Hooks: Unlock the ultimate automation tool. You will learn to create shell commands that trigger at specific events in Claude's lifecycle, enabling you to automate everything from running tests to formatting code and even calling other AI agents.
Sub-Agents: Design and build a team of specialized AI assistants. You'll learn how to create and manage sub-agents, each with its own unique context, tools, and system prompt, to handle specific tasks like code reviews, debugging, or security analysis.
Agentic Coding Principles
Claude Code Plugins
Claude Code Output Styles
Key Capabilities and Topics Covered
This course provides a deep dive into practical, real-world applications of Claude Code:
Advanced Context Engineering: Master the art of keeping Claude focused and efficient by managing its context window with /clear, /compact, and automated memory systems.
Multi-Agent Workflows: Design and implement complex workflows where specialized sub-agents collaborate to solve problems, orchestrated by Hooks and a central Claude instance.
Tool Use and Permissions: Securely grant Claude access to your local tools and scripts, and manage what it can and cannot do with granular permission controls.
IDE Integration: Set up and optimize the Claude Code extension in your IDE for a seamless workflow that combines terminal power with in-editor diffs and context.
Cost and Performance Optimization: Understand the tokenomics of Claude Code and learn best practices for managing cost and ensuring high-performance interactions.
Real-World Projects: Apply everything you've learned in hands-on projects, from building a custom linter with Hooks to creating a multi-agent system for automated code reviews.
Who this course is for:
Advanced GenAI Users: Users who are ready to go beyond the chat interface and leverage the full programmatic power of Claude Code.
AI Engineers: Professionals looking to build and deploy sophisticated, agentic workflows directly within their development environment.
Application Developers: Software engineers who want to automate repetitive tasks and integrate a deeply context-aware AI partner into their daily workflow.
Data Scientists: Practitioners aiming to automate complex data analysis, scripting, and pipeline generation tasks.
