Complete AI Learning Roadmap
A structured, topic-by-topic roadmap and resource collection for learning generative and agentic AI, moving from math and Python foundations through machine learning, deep learning, LangChain, RAG, vector databases, LangGraph and the Model Context Protocol.
This repository organizes a learning path across more than twenty topics, from math foundations, Python basics, Streamlit and FastAPI, through core and deep-dive machine learning, NLP and deep learning fundamentals, to generative AI, advanced large language models, LangChain, retrieval-augmented generation, vector databases and agentic AI.
Later sections cover MLOps, transformers, LangGraph and advanced agent patterns, the Model Context Protocol, fine-tuning and LLMOps, alongside additional agentic-framework and general resource sections. Each topic lists a short description and links to both Hindi- and English-language courses and videos.
The material is presented as Jupyter notebooks and links to external tutorials and courses rather than as a single self-contained course, and it targets learners moving from foundational concepts to advanced generative- and agentic-AI deployment.