Learn Agentic AI

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GitHub Jupyter Notebook MIT

Description

A comprehensive tutorial repository for learning AI agent development, covering OpenAI Agents SDK, LangGraph, MCP protocol, and more with hands-on projects.

Key Features

  • Comprehensive curriculum from agentic AI basics to cloud-native scaling
  • Hands-on projects with OpenAI Agents SDK, LangGraph, and MCP protocol
  • DACA design pattern: Kubernetes + Dapr + Ray for massive agent systems
  • Jupyter Notebook-based tutorials with progressive difficulty levels
  • Covers agent planning, tools, memory, evaluation, and safety guardrails
  • Part of the Panaversity Certified Agentic & Robotic AI Engineer program

Use Cases

πŸ’‘ Learn to design and build AI agents from fundamentals to production
πŸ’‘ Train teams on integrating AI into enterprise workflows with ROI focus
πŸ’‘ Build cloud-native agent systems scalable to millions of concurrent agents
πŸ’‘ Understand MCP, A2A, and NANDA protocols for interoperable agent architectures

Tags

tutorial agentic-ai langgraph mcp education

Categories

πŸ€– Agent Framework πŸ”Œ MCP Tools

Quick Start

Clone the repo and start with the introductory Jupyter notebooks. Prerequisites: Python, basic ML knowledge. Follow the learning path from simple agent examples through LangGraph and OpenAI Agents SDK projects. Each module includes code, explanations, and hands-on exercises.
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