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Agentic AI – Fundamentals

Welcome to the Agentic AI learning resource! Built in collaboration with SuperDataScience, this course is part of our community-driven effort to make Agentic AI accessible to everyone.

This repository is your hands-on guide to building AI agents from scratch using pure Python before we move on to frameworks like LangChain or CrewAI. By the end of these courses, you’ll understand how agents work under the hood and be able to build autonomous Agentic AI systems and deploy them to production for scalability.


About This Repository

This repository contains step-by-step Python scripts and Jupyter notebooks that introduce you to the core ideas of Agentic AI. You’ll build agents incrementally, starting from a simple loop around an LLM, and progressing toward agents with tools, reasoning traces, and error handling.

What You'll Learn

  • What AI agents are and how they differ from plain LLMs
  • Building a basic agent loop in Python
  • Adding tools (calculator, search, APIs) to agents
  • Handling errors and retries
  • A mini project: An AI Travel Planner

🗂️ Repository Structure

agentic-ai/
├── README.md
├── requirements.txt
├── environment.yaml
├── .env.example
└── Part1-Fundamentals/
    └── community-contributions/
    └── lab1
    └── lab2

🚀 Getting Started

To set up your environment, please follow the step-by-step instructions for your operating system:

These guides cover prerequisites, repo cloning, environment setup, API key configuration, and troubleshooting tips.

Once your environment is ready, you can start learning by launching the notebooks in the Part1-Fundamentals/ folder.


🛠️ Key Dependencies

  • OpenAI – for accessing LLMs
  • python-dotenv – for managing API keys in .env
  • Jupyter – for interactive learning

🤝 Contributing

We welcome contributions from the community!

Ways to Contribute

  1. Report issues or suggest improvements
  2. Improve documentation
  3. Add new agent examples or tools
  4. Fix bugs in notebooks

Guidelines

  • Fork the repo and create a feature branch
  • Follow the existing code style and notebook format
  • Add clear markdown explanations and comments
  • Test your notebooks before submitting
  • Open a pull request with a clear description

Community submissions go in the community-contributions/ folder.


📚 Additional Resources


📢 Need Help?


Happy Learning! 🎉 Start your Agentic AI journey today and build your own Python-powered agents from scratch.

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This repo serves as a central repository for our course lectures around the concepts of Agentic AI

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