Master the rapidly growing field of AI agent building, where developers create AI systems that think and act independently. This learning path helps Python developers, automation engineers, and ML practitioners get ready to create the next generation of intelligent applications. Learn how to architect multi-agent systems that collaborate and solve complex problems autonomously using cutting-edge frameworks like LangGraph, LlamaIndex, and Model Context Protocol.
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Create autonomous AI agents using LangGraph and LlamaIndex.
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Build multi-agent systems with MCP and A2A protocols.
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Deploy production-ready agents that automate workflows.
Courses
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1
Build AI Agents and Automate Workflows with n8n50mBuild AI Agents and Automate Workflows with n8n
By: Morten Rand-Hendriksen
Create advanced AI-powered workflow automations to add agentic behaviours to your existing tools in the cloud, on prem, or on your computer with n8n.
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2
Build AI Agents and Chatbots with LangGraph1h 14mBuild AI Agents and Chatbots with LangGraph
By: Kumaran Ponnambalam
Build agentic AI powered chatbots with LangGraph that deliver sophisticated conversations and autonomy for user engagements.
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3
Model Context Protocol (MCP): Hands-On with Agentic AI55mModel Context Protocol (MCP): Hands-On with Agentic AI
By: Morten Rand-Hendriksen
Use the Model Context Protocol (MCP) to build a universal interface connecting data, services, and custom tools to AI agents.
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4
Hands-On AI: Building AI Agents with Model Context Protocol (MCP) and Agent2Agent (A2A)1h 40mHands-On AI: Building AI Agents with Model Context Protocol (MCP) and Agent2Agent (A2A)
By: Kumaran Ponnambalam
This course equips you to design, build, and deploy intelligent AI agents using Model Context Protocol (MCP) and Agent2Agent (A2A) frameworks.