AI Agent Mastery Course

This repository contains all code and resources for the AI Agent Mastery course. This comprehensive course guides you through the full lifecycle of building AI agents—from initial planning to deployment and monetization!

Current Available Content

Currently, the repository includes:

Module 3: Prototyping with No-Code (n8n)

• Complete n8n workflows for rapid AI agent prototyping
• JSON workflow files ready to import into your n8n instance
• Example configurations for different use cases
• Step-by-step setup instructions
• Local AI and "Cloud" AI implementations

Module 4: Building & Coding the Agent

• Pydantic AI code examples for structured AI agent development
• Complete Python implementations of agent components
• Configuration scaffolding to use your agents with any LLMs (local and not local)
• RAG (Retrieval Augmented Generation) implementation patterns
• Best practices for agent long term memory
• Examples for using your AI agents in a frontend (built with Streamlit)

Module 5: Agent Application (Full UI)

• Full-stack application with React frontend and FastAPI backend
• Modern UI with Shadcn components and real-time streaming responses
• Conversation history management and storage
• User session management
• Integration with the Pydantic AI agent from Module 4
• Optional n8n backend integration with the Module 3 agents

Module 6: Agent Deployment & Production

• Modular containerization architecture with Docker
• Production-ready deployment configurations for multiple cloud platforms
• Complete CI/CD workflows with GitHub Actions
• Multiple deployment strategies: DigitalOcean, Render, and Google Cloud Platform with Terraform
• Agent observability and monitoring with Langfuse integration

Mock Data for RAG

If you want a collection of documents (Markdown files) for a fake company generated by Claude like I use in the course and on YouTube, feel free to download Mock_Data_For_RAG.zip and bring that into your file source for your RAG pipeline.

How to Use the Course Materials

1. Select the module you're currently working on (each folder starts with the module number)
2. Review the README in each module folder for specific setup instructions
3. Follow along with the corresponding course videos while exploring the code or workflows

Getting Started

To get started with the course materials:

# Clone the repository (if you haven't already)
git clone https://github.com/dynamous-community/ai-agent-mastery.git

# Navigate to the course directory
cd ai-agent-mastery

# Explore the available modules
ls (or dir on windows)

Coming Soon

Additional modules will be added to the repository as they are released (schedule is finalized!):

• Module 7: Advanced Agent Architecture (Multi-Agent, Guardrails, etc.)
• Module 8: Agent Testing and Evaluation
• Module 9: Monetizing AI Agents
• Module 10: Next Steps & Bonus Resources

Support & Questions

If you have questions about the code/workflows or encounter any issues:

• Check the dedicated discussions in the Dynamous community
• Join live workshops where we'll be covering many topics to dive deeper into building specific components of AI agents
• Join our live Q&A sessions for direct support

LICENSE

As stated in the main README for the Dynamous Community Organization, all code, resources, workflows, and templates are governed by the proprietary Dynamous LICENSE.