This repository provides a structured roadmap for learning Agentic AI, targeting individuals looking to build advanced AI systems. It offers a comprehensive learning path from foundational programming and machine learning concepts to advanced generative AI, multi-modal RAGs, and specific agentic AI frameworks, culminating in cloud integration.

How It Works

The roadmap outlines a progressive learning journey, starting with Python and fundamental Machine Learning/NLP concepts. It then delves into Deep Learning for NLP, Generative AI, and specific agentic AI frameworks like Langchain, LangGraph, Phidata, CrewAI, and Autogen. The curriculum also includes Generative AI integration with major cloud platforms (AWS, Azure) and the Model Context Protocol (MCP).

Quick Start & Requirements

• Prerequisites: Python programming, basic Machine Learning, Natural Language Processing (NLP), Deep Learning for NLP, Generative AI concepts.
• Frameworks Covered: Langchain, LangGraph, Phidata, CrewAI, Autogen.
• Cloud Platforms: AWS, Azure.
• Additional: Model Context Protocol (MCP).
• Learning Resource: A bootcamp is offered with admission details and contact information provided.

Highlighted Details

• Covers foundational to advanced topics in Agentic AI.
• Includes practical projects and end-to-end tutorials.
• Features popular agentic AI frameworks and cloud integrations.
• Offers a structured learning path with mentorship.

Maintenance & Community

The roadmap is associated with Krish Naik's academy, with specific mentors listed. Contact information for queries is provided.

Licensing & Compatibility

No licensing information is provided in the README.

Limitations & Caveats

The repository itself is a roadmap and does not contain code; it directs users to external resources and a paid bootcamp. The bootcamp details (start date, timing, duration, cost) are not specified beyond the admission link.