Roadmap To Learn Agentic AI

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Basic Information

This repository is a curated roadmap for learning how to build agentic AI systems. It organizes topics and study paths for people who want to understand and implement autonomous, multi-step AI agents. The README lists prerequisites and sequential learning modules including Python programming, basic machine learning and NLP concepts, deep learning for NLP with transformer explanations, generative AI tutorials with end-to-end projects, and multi-modal retrieval-augmented generation. It also highlights important agentic frameworks and infrastructure such as LangChain, LangGraph, Agno/Phidata, CrewAI, Autogen, and the Model Context Protocol. The repo serves as an educational index of playlists, tutorials, framework recommendations, and cloud-focused guidance (AWS, GCP, Azure) aimed at helping learners progress from fundamentals to agentic system development.

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Features
The README is organized into clear sections: prerequisites, Python, basic ML/NLP, deep learning for NLP, generative AI projects, agentic frameworks, cloud integration, and the Model Context Protocol. It references curated video playlists and tutorials for each topic, specific framework recommendations (LangChain, LangGraph, Agno/Phidata, CrewAI, Autogen), and mentions multi-modal RAG and MCP as practical topics. The document also calls out cloud-specific learning paths for AWS, Azure, and GCP and includes a live bootcamp announcement with schedule, duration, and listed mentors. Visual badges and images accompany many sections to indicate resources and playlists. The structure prioritizes a stepwise progression and points learners to concrete resources and tooling to explore further.
Use Cases
This roadmap helps learners by providing a structured study plan and a consolidated list of resources to move from programming basics to building agentic AI. It highlights the practical technologies and frameworks to focus on, points to generative AI projects and multi-modal RAG strategies for hands-on experience, and emphasizes cloud integration for deployment considerations. The repo also introduces Model Context Protocol for context handling in agentic systems. For those seeking guided instruction, the README advertises a live bootcamp with dates, times, duration, and mentors, enabling learners to access mentorship and an applied curriculum. Overall, it reduces discovery time and helps prioritize which tools and concepts to learn to build agentic AI systems.

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