The Agentic AI Engineering Masterclass 2026
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Unclaimed ProfileThe Agentic AI Engineering Masterclass 2026, crafted by Prof. Ryan Ahmed, stands as a premier guide for developers, automation specialists, and tech enthusiasts aiming to master the future of autonomous systems. This comprehensive program delves deep into the cutting-edge landscape of AI Agents, equipping learners with the practical skills required to build, orchestrate, and deploy highly sophisticated, multi-agent workflows. Throughout this course, you will gain hands-on experience with industry-standard frameworks and protocols, including the OpenAI Agents SDK, LangGraph, CrewAI, AutoGen, and the revolutionary Model Context Protocol (MCP). By working through real-world scenarios, you will learn to implement robust handoff mechanisms, design memory-enabled systems, enforce behavioral guardrails, and leverage low-code platforms like n8n for seamless integrations with tools such as Gmail, Slack, and Google Sheets. Whether you are aiming to design collaborative AI teams, configure multi-model environments containing GPT, Claude, and Gemini, or deploy human-in-the-loop validation systems, this masterclass provides the architectural blueprint and practical coding exercises to elevate your engineering career into the high-demand arena of cognitive automation.
About the creator
Prof. Ryan Ahmed
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Prof. Ryan Ahmed is a distinguished educator and technology leader dedicated to making artificial intelligence and machine learning accessible to a global audience. With a profound understanding of cutting-edge tech, Ryan specializes in demystifying complex concepts such as Agentic AI engineering, LLM system architecture, and advanced retrieval-augmented generation (RAG). His teaching methodology centers on a practical, hands-on approach that bridges the gap between theoretical data science and enterprise-ready application development. Whether guiding his students through building custom Python-based AI agents from scratch or configuring enterprise workflows using Microsoft Copilot Studio, Ryan ensures every lesson is grounded in real-world utility. He…Show more
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Program Overview
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Learning format
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Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Build and deploy intelligent autonomous AI agents using cutting-edge frameworks like OpenAI Agents SDK, N8N, AutoGen, CrewAI, LangGraph, & MCP.
- Build AI agents that remember, reason, and collaborate using memory, tools, guardrails, and handoffs.
- Learn the foundational components of the OpenAI Agents SDK, including the Agent object and Runner class.
- Build and run AI agents and monitor their activity using traces on the OpenAI API platform.
- Build handoff mechanisms that smoothly transfer context and inputs between agents (e.g., Planner → Writer).
- Implement guardrails to enforce boundaries (e.g., preventing responses on restricted topics like politics).
- Explore CrewAI for building more advanced agentic workflows and extend agents with custom Python execution tools for analysis and modeling.
- Grasp the fundamentals of multi-model AI agents in AutoGen and build teams of agents using different LLMs (e.g., GPT, Gemini, Claude).
- Understand how to design agentic workflows in LangGraph, including connecting them to interfaces like Gradio for user interaction.
- Use n8n for low-code automation, building AI-powered flows that integrate with Google Sheets, Calendar, and Gmail.
- Learn the principles of the Model Context Protocol (MCP) for tool interoperability and build agents that interact with MCP services.
- Build manager functions to orchestrate multi-agent workflows from input to final deliverable.
- Build AI agents that integrate Tavily web search for structured, real-time search results.
- Extend agents by integrating OpenAI tools (e.g., Code Interpreter) and combining real-time search, memory, and reasoning into workflows.
- Apply memory-enabled agents to real use cases (e.g., market research assistant) for multi-turn queries.
- Develop a library of specialist agents (Planner, Writer, Analyst, Search Agent) and coordinate their interactions.
- Create collaborative agent teams for real-world tasks like marketing strategy, with the option of adding a human-in-the-loop User Proxy for oversight.
- Build domain-specific LangGraph agents (e.g., flights and hotel booking) and define custom tools for task-specific workflows.
- Create tools as agents by wrapping autonomous agents behind a function-tool interface, enabling seamless invocation by others.
- Design a multi-agent research assistant that can triage queries, delegate tasks, and generate executive-ready reports.
- Design creative multi-agent pipelines for advertising campaigns, with role-specific agents like Creative Director, Strategist, and Copywriter.
- Create and deploy Gradio-based MCP tools as standardized services accessible to agents.
- Create collaborative agent teams for real-world tasks like marketing strategy, with the option of adding a human-in-the-loop User Proxy for oversight.
Best For
- Software engineers and developers looking to pivot into AI agent design and multi-agent orchestration.
- Automation specialists who want to leverage frameworks like LangGraph and CrewAI to build autonomous workflows.
- Tech professionals aiming to integrate LLMs like GPT-4, Claude, and Gemini into enterprise-grade software systems.
- Data scientists and engineers interested in implementing human-in-the-loop validation and behavioral guardrails.
Not For
- Complete beginners with no prior experience in programming or Python development.
- Individuals seeking a conceptual, high-level overview of AI without interest in writing code or building technical workflows.
- Professionals strictly looking for no-code AI chatbot tools who do not wish to learn about agentic architecture or SDKs.
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