Course Modules

Detailed breakdown of all 10 modules

Part 1: Vibe Coding Basics

Module 1

Introduction to AI-Powered Development

Learning Objectives:

  • Understand what "Vibe Coding" means
  • Learn how AI is transforming software development
  • Get familiar with AI coding assistants
  • Set up your AI development environment

Topics Covered:

  • What is Vibe Coding?
  • Evolution of software development with AI
  • Understanding AI coding assistants
  • Setting up your environment
View Module Materials
Module 2

Working with AI Coding Tools

Learning Objectives:

  • Master popular AI coding tools
  • Learn prompt engineering for developers
  • Understand best practices for AI-assisted coding
  • Write effective prompts for code generation

Tools Covered:

  • GitHub Copilot
  • Cursor AI
  • ChatGPT for coding
  • Prompt engineering techniques
View Module Materials
Module 3

Practical Vibe Coding Techniques

Learning Objectives:

  • Generate production-quality code with AI
  • Refactor existing code using AI assistance
  • Debug efficiently with AI support
  • Create comprehensive documentation
  • Generate test cases automatically

Techniques:

  • Code generation with AI assistants
  • Refactoring with AI
  • AI-assisted debugging
  • Documentation generation
  • Test generation
View Module Materials
Module 4

Hands-On Lab - Building Your First AI-Assisted Project

Project Goal:

Build a complete application using AI-assisted development from start to finish.

Project Options:

  • Task Management API
  • Weather Dashboard
  • Blog Platform
  • Or your own idea!
View Lab Instructions

Part 2: AI Agents + Tools

Module 5

Introduction to AI Agents

Learning Objectives:

  • Understand what AI agents are
  • Identify different types of AI agents
  • Learn agent architectures and patterns
  • Recognize use cases for AI agents in development

Agent Types:

  • Reactive agents
  • Goal-based agents
  • Learning agents
  • Multi-agent systems
View Module Materials
Module 6

Building AI Agents

Learning Objectives:

  • Build AI agents using popular frameworks
  • Understand agent components and architecture
  • Implement memory systems for agents
  • Integrate tools and APIs into agents

Frameworks:

  • LangChain for Agents
  • AutoGPT concepts
  • Custom agent development
  • Agent components: memory, tools, logic
View Module Materials
Module 7

AI Tools Ecosystem

Learning Objectives:

  • Understand the landscape of AI development tools
  • Learn to integrate AI into CI/CD pipelines
  • Use automated testing agents
  • Generate documentation automatically

Tools Categories:

  • Code analysis tools
  • Automated testing agents
  • Documentation generators
  • CI/CD integration
  • Monitoring and logging
View Module Materials
Module 8

Advanced AI Agent Patterns

Learning Objectives:

  • Design and implement multi-agent systems
  • Create agent collaboration patterns
  • Handle errors and recovery in agents
  • Optimize agent performance
  • Address security considerations

Advanced Topics:

  • Multi-agent systems
  • Agent collaboration patterns
  • Error handling and recovery
  • Performance optimization
  • Security best practices
View Module Materials
Module 9

Hands-On Lab - Building a Development AI Agent

Final Project Goal:

Design, build, and deploy a fully functional AI agent that solves a real development workflow problem.

Project Options:

  • PR Review Agent
  • Documentation Maintenance Agent
  • Test Coverage Agent
  • DevOps Monitoring Agent
  • Custom agent (your idea!)
View Lab Instructions
Module 10

Best Practices & Future of AI in Development

Learning Objectives:

  • Understand ethical considerations in AI coding
  • Recognize limitations and challenges
  • Learn strategies for staying current
  • Explore future trends in AI development
  • Build your personal AI toolkit

Key Topics:

  • AI coding ethics and responsible use
  • Limitations and challenges
  • Staying updated with AI tools
  • Future trends
  • Building your personal toolkit
View Module Materials

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