Agentic AI Course | Build Agents with LangChain & LangGraph

About this course

AI is evolving beyond systems that simply generate responses. Agentic AI enables AI systems to work through tasks, interact with information, and perform actions with greater autonomy.

This course provides a practical introduction to Agentic AI, AI agents, Generative AI, and LLM-powered applications. You’ll begin with Python and Generative AI fundamentals before progressing into prompt engineering, LangChain, AI agents, Agentic RAG, and LangGraph.

As you advance, you’ll explore multi-agent design and work with popular AI agent frameworks including AutoGen, CrewAI, Smol Agents, and LlamaIndex. You’ll also learn the fundamentals of MCP in Agentic AI, along with deployment strategies, APIs, hardware requirements, and model serving.

The course focuses on practical learning through coding exercises and Agentic AI projects, helping you understand how different components come together to create intelligent AI applications.

By the end of the course, you’ll have practical exposure to building AI agents, developing Agentic RAG applications, designing multi-agent workflows, and working with modern frameworks used in the Agentic AI ecosystem.

Benefits

Learn by Practising – Develop AI agents and work on practical coding exercises and projects.

End-to-End Learning – Progress from Python and Generative AI fundamentals to Agentic AI development and deployment.

Industry-Relevant Technologies – Gain hands-on exposure to LangChain, LangGraph, AutoGen, CrewAI, Smol Agents, and LlamaIndex.

Practical AI Skills – Learn how AI agents, RAG systems, and multi-agent workflows are developed.

Future-Ready Knowledge – Build skills around one of the rapidly evolving areas of Generative AI.

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