Udemy – AI Agents Crash Course: Build with Python & OpenAI

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 build a smart nutrition assistant that:

• Uses OpenAI’s Agents SDK to understand and respond to prompts
• Calls external tools and APIs
• Leverages 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this hands-on course gives you a complete end-to-end agentic AI foundation — without getting buried in theory or outdated code.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 SDK
• Tool 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:

• Engineers and developers with basic Python experience
• AI/ML professionals looking to quickly learn agent orchestration
• Product builders and technical leads exploring agentic workflows
• Learners who want to build, not just read about agents

About the Instructors: Your instructors combine deep industry experience with a passion for clear, actionable teaching. Frank Kane spent 9 years at Amazon and IMDb, where he built large-scale recommender systems and led engineering teams. He holds 17 patents in machine learning and distributed systems and has taught over 1 million students through his company, Sundog Education.

DOWNLOAD LINK: AI Agents Crash Course: Build with Python & OpenAI

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