Build AI Agents with OpenAI SDK Build Real Agentic AI

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Build AI Agents with OpenAI SDK Build Real Agentic AI
Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 7m | Size: 965.68 MB
A Hands-On Guide to Building, Debugging, and Deploying Intelligent AI Agents with Tools, RAG, MCP & Multi-Agent Workflow

What you'll learn
Build AI agents from scratch using the OpenAI Agents SDK and Python.
Create real-world agent capabilities using function tools and tool calling.
Use OpenAI Tracing and observability to debug agent workflows, LLM calls, and tool calls.
Build advanced agentic AI applications using RAG, MCP, and multi-agent architectures.
Requirements
Basic Python programming knowledge is recommended.
Basic understanding of APIs and JSON will be helpful, but is not required.
An OpenAI API key to run the hands-on examples. API usage may incur a small cost.
No prior experience with AI agents, Agentic AI, RAG, MCP, or multi-agent systems is required.
Description
Want to move beyond basic ChatGPT prompts and learn how to buildreal AI agents?
Welcome toMaster AI Agents with OpenAI SDK: Build Real Agentic AI- a practical, hands-on course where you'll learn how to build intelligent agentic applications using theOpenAI Agents SDK.
We'll start from the fundamentals and gradually build more capable AI agents. You'll learn how to create agents with the OpenAI SDK, provide instructions, execute agents using Runner, and give them real capabilities throughtool calling.
We'll exploreOpenAI Tracing and observability so you can see exactly what happens inside your agent - including LLM calls, tool calls, and execution flows.
As we progress, we'll expand our agents withRAG, MCP, and multi-agent architectures, building toward real-world agentic AI applications.
This course is designed to be practical and beginner-friendly, with working examples, hands-on coding, quizzes, and clear explanations throughout.
This course is designed to be practical and beginner-friendly, with working examples, hands-on coding, quizzes, and clear explanations throughout. You'll learn by building rather than simply watching theory, allowing you to understand not onlyhow agents work, but alsowhy different architectural decisions matter.
By the end, you won't just understand what agentic AI is -you'll know how to build it.
Who this course is for
Python developers who want to learn how to build AI agents and Agentic AI applications.
Software developers and engineers looking to integrate LLMs into real-world applications.
AI/ML engineers who want hands-on experience with the OpenAI Agents SDK.
Beginners in Agentic AI who want a practical, step-by-step introduction to agents, tools, RAG, MCP, and multi-agent systems.
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