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Course Outline
Introduction to Claude Code
- What Claude Code is and how it differs from copilots
- Key features: codebase understanding, multi-file editing, terminal integration
- Overview of the agent loop and planning capabilities
Installation and Configuration
- Installing Claude Code via npm and official packages
- Setting up API keys and authentication for Anthropic models
- Terminal configuration and IDE plugin options
- Managing context windows and token limits
Navigating Codebases with Natural Language
- Using search and query commands across files
- Understanding file relationships and dependencies
- Refactoring and restructuring code with prompts
Multi-File Editing Workflows
- Building features that span multiple files
- Cross-file dependency management
- Testing and validation after automated edits
Approval Modes and Security
- Automatic, semi-automatic, and manual approval levels
- Setting boundaries for agent autonomy
- Reviewing changes before application in production contexts
Git Integration
- Initiating branches and commits with Claude Code
- Diff review and merge conflict assistance
- Commit message generation and changelog creation
Debugging and Bug Fixing
- Identifying root causes across the codebase
- Applying targeted patches and running tests
- Using the agent for regression testing
Team and Enterprise Features
- Shared context and team-specific configurations
- Custom rules and style enforcement
- Enterprise deployment patterns and SSO considerations
CI/CD and Automation Workflows
- Triggering agent tasks from pipeline events
- Pre-commit checks and automated code review
- Running Claude Code in headless and CI environments
Performance Optimization
- Managing large codebases within context limits
- Splitting workloads and caching session data
- Choosing the right model tier for the task
Troubleshooting
- Resolving common connection and auth issues
- Debugging agent misinterpretations and bad edits
- Handling rate limits and token exhaustion
Security and Compliance
- Data handling and privacy considerations
- Managing sensitive credentials and secrets in agent context
- Enterprise audit trails and governance
Summary and Next Steps
- Recap of key features and workflows
- Resources for continued learning and community support
- Transition to advanced Claude Code topics
Requirements
- Experience with software development in at least one programming language
- Basic command-line and terminal usage
- Familiarity with Git and version control workflows
Audience
- Software developers looking to accelerate development with agentic AI
- Engineering leads evaluating AI-assisted coding tools for teams
- DevOps engineers integrating AI agents into CI/CD workflows
14 Hours
