Learn to build agentic AI solutions using Python, OpenAI SDK, tools, memory, RAG, and guardrails – in just four hours!
Description
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.
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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:
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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this hands-on course gives you a complete end-to-end agentic AI foundation — without getting buried in theory or outdated code.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.
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.
| Total Students | 551 |
|---|---|
| Duration | 2.5 hours |
| Language | English (US) |
| Original Price | |
| Sale Price | 0 |
| Number of lectures | 33 |
| Number of quizzes | 3 |
| Total Reviews | 16 |
| Global Rating | 4.84375 |
| Instructor Name | Sundog Education by Frank Kane |
Course Insights (for Students)
Actionable, non-generic pointers before you enroll
Student Satisfaction
86% positive recent sentiment
Momentum
Steady interest
Time & Value
- Est. time: 2.5 hours
- Practical value: 8/10
Roadmap Fit
- Beginner → Beginner → Advanced
Key Takeaways for Learners
- Best Practices
- Analytics
- Hands On
- Concise
Course Review Summary
Signals distilled from the latest Udemy reviews
What learners praise
- Hands On
- Concise
- Clear Explanation
Watch-outs
No consistent issues reported.
Difficulty
Best suited for
New learners starting from zero
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