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 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 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this hands-on course gives you a complete end-to-end agentic AI foundation -- without getting buried in theory or outdated code.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 - Visually developing and deploying agentic systems with AgentKit, AgentBuilder, ChatKit, and Evals - 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. Zoltan C. Toth brings over two decades of experience in AI infrastructure and data systems. As a former principal instructor and Solutions Architect Databricks and Data Engineering lead at startups, he’s helped companies around the world scale their analytics and AI platforms. Zoltan also teaches AI and data engineering at the Central European University. Together, Frank and Zoltan guide you step-by-step through building agents the right way: with real code, real tools, and production-ready techniques. Ready to build your first AI agent, fast? Enroll now and start building today.