📚 Learning Roadmap

Welcome to my learning repository! This document provides a structured overview of the courses and hands-on projects I'm currently working through, with links to interactive notebooks, code repositories, and notes.

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🤖 Agentic AI: Hands-On Learning Track

This track focuses on building autonomous and interactive AI agents using modern large language model (LLM) frameworks. Each module includes theory, implementation, and practical exercises.

💡 Inspired by *The Illustrated Course by Krish Naik.

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📘 Table of Contents

Chapter	Topic	Notebook/Repo Link
1	✅ Agentic AI Tutorial Introduction	GitHub
*	✅ Assignemnt-0	GitHub
2	✅ LangChain Document Loaders and Text Splitters	GitHub
3	✅ Text Embeddings & Retrieval with LangChain: OpenAI, Hugging Face, FAISS, and Classic RAG	GitHub
*	✅ Assignemnt-1	GitHub
4	✅ LangChain Tools & LangGraph Integration Tutorial-1	GitHub
5	✅ LangChain Tools & LangGraph Integration Tutorial-2	GitHub
*	✅ Assignment-2	GitHub
6	✅ Agent RAG Pipeline	GitHub
*	✅ Assignment-3 "AI-Based Trip Planner with Agentic AI"	GitHub
7	✅ Introduction of Multi Agent	GitHub
*	✅ Assignemnt-4	GitHub
8	✅ LangGraph Multi-Agent & Human-in-the-Loop Agent	GitHub
*	✅ Assignemnt-5	GitHub
9	✅ Introduction of Autogen	GitHub
10	✅ Basic of Autogen	GitHub
11	✅ Autogen Teams	GitHub
12	✅ Human in Loop	GitHub
13	✅ Autogen Teams-selector	GitHub
-	🕐 In Progress	Coming soon

✅ Completed  🕐 In Progress  🔜 Planned

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🛠️ Tech Stack

This series leverages the following tools and technologies:

• Frameworks: LangChain, LangGraph
• LLM APIs: OpenAI, LLaMA, Mistral
• Memory / Vector Stores: FAISS, ChromaDB
• Backend & Deployment: Python, FastAPI, Streamlit

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📝 Notes & Resources

• All detailed notes are available in the notes/ directory of the repo.
• Each notebook is self-contained with markdown explanations, code, and outputs.
• Bonus content and diagrams will be available under the extras/ folder.