AI Agents Crash Course: Build with Python & OpenAI

About this course

Building intelligent AI agents can feel overwhelming. Between OpenAI’s complex SDK, retrieval-augmented generation (RAG), tool-calling, memory, and prompt engineering, it’s hard to know where to start.

This crash course is your shortcut: in just a few hours, you'll go from zero to deploying your own functional, real-world agentic AI system. You'll go hands-on building agentic AI systems with Python, and also visually in the no-code AgentBuilder environment.

You’ll build a smart nutrition assistant that:

• Uses OpenAI’s Agents SDK and AgentKit to understand and respond to prompts
• Calls external tools and APIsLeverages memory and RAG for contextual intelligence
• Includes guardrails to behave safely and reliably
• Can be deployed to the cloud with authentication

Whether you're a developer, data scientist, or AI-curious engineer, this hands-on course gives you a complete end-to-end agentic AI foundation -- without getting buried in theory or outdated code.

What You’ll Learn

How to build AI agents with Python + OpenAI’s Agents SDKVisually developing and deploying agentic systems with AgentKit, AgentBuilder, ChatKit, and EvalsTool calling, streaming, and tracing techniques

Best practices in prompt engineering and context design

How to integrate memory and RAG for deeper contextual reasoning

Deploying your agent securely with authentication and guardrails

How to build multi-agent systems with task delegation and parallel execution

Who This Course is For<

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