Agentic AI Nano-Degree¶

Welcome to the comprehensive Agentic AI Nano-Degree program! This intensive curriculum covers the complete landscape of modern AI agent development and Retrieval-Augmented Generation (RAG) systems.

Nano-Degree in Agentic AI

🚀 Getting Started¶

Ready to begin your learning journey? Choose your path based on your setup and learning preferences:

Program Overview¶

This nano-degree consists of three comprehensive modules designed to take you from fundamentals to production-ready implementations:

Module 1: Agent Frameworks (10 Sessions)¶

Master the art of building intelligent agents using cutting-edge frameworks and patterns.

What You'll Learn¶

• Bare metal agent implementation patterns
• LangChain and LangGraph workflow orchestration
• CrewAI team-based agent coordination
• PydanticAI type-safe agent development
• Atomic Agents modular architecture
• ADK (Agent Development Kit) integration
• Agno production-ready deployment
• Multi-agent coordination patterns
• Enterprise integration strategies

Module 2: RAG Architecture (10 Sessions)¶

Build sophisticated Retrieval-Augmented Generation systems for enterprise applications.

What You'll Learn¶

• RAG architecture fundamentals and evolution
• Advanced chunking and preprocessing strategies
• Vector database optimization techniques
• Query enhancement and context augmentation
• RAG evaluation and quality assessment
• Graph-based RAG implementations
• Agentic RAG systems
• Multi-modal RAG architectures
• Production deployment and enterprise integration

Module 3: MCP, ACP & Agent-to-Agent Communication (10 Sessions)¶

Master the Model Context Protocol, Agent Communication Protocol, and sophisticated agent-to-agent communication patterns.

What You'll Learn¶

• MCP (Model Context Protocol) fundamentals and server development
• Secure MCP implementations with authentication and authorization
• ACP (Agent Communication Protocol) architecture and patterns
• Agent-to-agent communication strategies and coordination
• Advanced agent workflow orchestration
• Production deployment of agent communication systems
• Security and compliance in multi-agent environments
• Enterprise integration of communication protocols
• Scalable agent coordination architectures

Learning Paths¶

Each session offers three distinct learning paths to accommodate different learning styles and time commitments:

👀 Observer Path (30-50 min)¶

• Focus: Conceptual understanding
• Activities: Read core concepts, examine patterns
• Ideal for: Quick overview, decision makers, time-constrained learners

🙋‍♂️ Participant Path (60-90 min)¶

• Focus: Guided implementation
• Activities: Follow exercises, analyze examples
• Ideal for: Active learners, developers, technical managers

🛠️ Implementer Path (120-180 min)¶

• Focus: Hands-on development
• Activities: Build systems, explore advanced patterns
• Ideal for: Engineers, architects, deep technical expertise

Prerequisites¶

Technical Background¶

• Intermediate Python programming experience
• Basic understanding of APIs and web services
• Familiarity with Git and command-line tools
• Understanding of basic machine learning concepts

Recommended Knowledge¶

• Experience with REST APIs
• Basic knowledge of databases
• Understanding of cloud computing concepts
• Familiarity with containerization (Docker)

Learning Outcomes¶

Is it agentic?

Upon completion of this nano-degree, you will be able to:

Agent Development¶

• Design and implement sophisticated AI agents using multiple frameworks
• Create multi-agent systems with proper coordination and communication
• Deploy production-ready agents with monitoring and scaling capabilities
• Integrate agents into enterprise workflows and systems

RAG Systems¶

• Architect and build comprehensive RAG systems from scratch
• Implement advanced retrieval strategies and query optimization
• Evaluate and improve RAG system performance and accuracy
• Deploy enterprise-grade RAG solutions with proper security and compliance

Agent Communication & Protocols¶

• Master MCP and ACP protocol implementations
• Build secure, scalable agent-to-agent communication systems
• Design sophisticated multi-agent coordination patterns
• Deploy enterprise-grade agent communication infrastructures

Tools & Technologies¶

Frameworks & Libraries¶

• LangChain & LangGraph
• CrewAI
• PydanticAI
• Atomic Agents
• ADK (Agent Development Kit)
• Agno

RAG Technologies¶

• Vector databases (Chroma, Pinecone, Weaviate)
• Embedding models (OpenAI, Sentence Transformers)
• LLMs (GPT-4, Claude, Llama)
• Graph databases (Neo4j)
• Search engines (Elasticsearch)

Infrastructure¶

• Docker & Kubernetes
• GitHub Actions
• Cloud platforms (AWS, GCP, Azure)
• Monitoring tools (Prometheus, Grafana)

Course Structure¶

Each session follows a consistent structure:

1. Learning Navigation Hub - Choose your path and time investment
2. Core Content - Essential concepts and implementations (required)
3. Optional Modules - Deep-dive topics for advanced learners
4. Hands-on Exercises - Practical implementation experience
5. Assessment - Multiple choice tests with detailed solutions
6. Navigation - Clear paths to previous/next sessions

Choose Your Learning Module¶

Ready to begin your journey? Select the module that best fits your learning goals:

Study Tips¶

For Best Results¶

• Complete sessions in order within each module
• Practice with the provided code examples
• Implement the exercises in your own environment
• Join the community discussions and share your progress
• Take breaks between intensive sessions

Time Management¶

• 👀 Observer Path: 1 session every 2-3 days (30-50 min each)
• 🙋‍♂️ Participant Path: 1 session per day (60-90 min each)
• 🛠️ Implementer Path: 2-3 sessions per day (120-180 min each)

Community & Support¶

• GitHub Discussions: Ask questions and share insights
• Code Examples: All implementations available in the repository
• Regular Updates: Course content updated with latest best practices
• Community Contributions: Welcome improvements and additions

Ready to become an expert in Agentic AI? Choose your path and start your journey today!

Get Started with Agent Frameworks → Explore RAG Architecture → Master Agent Communication →