What you'll learn:
- Build functional AI agents using Python and the OpenAI SDK
- Implement tool calling, memory, and streaming responses in your agents
- Use prompt engineering and context engineering to control agent behavior
- Integrate Retrieval-Augmented Generation (RAG) using embedding databases
- Enforce safety with guardrails and prompt adherence techniques
- Orchestrate multi-agent systems with task decomposition and hand-offs
- Deploy AI agents to the cloud with authentication and secure setup
- Trace and debug agent behavior using OpenAI’s built-in tools
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 withPython, and also visually in the no-codeAgentBuilder environment.
You’ll build a smart nutrition assistant that:
Uses OpenAI’s Agents SDK andAgentKit 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this hands-on course gives you a complete end-to-end agentic AI foundation -- without getting buried in theory or outdated code.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, andEvals
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.
