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Unclaimed ProfileThe AI Agents Crash Course: Build with Python & OpenAI, created by Frank Kane and Sundog Education, provides a highly practical, fast-paced pathway for developers and tech professionals aiming to master the next generation of artificial intelligence. As the industry shifts from static LLM prompts to dynamic, autonomous agents, this course delivers the essential skills needed to build robust, agentic AI systems. Throughout the curriculum, learners dive deep into the OpenAI SDK and Python, exploring core concepts like tool calling, persistent memory, and streaming responses. Beyond the basics, the course addresses critical production challenges, teaching students how to implement Retrieval-Augmented Generation (RAG) using embedding databases, enforce system safety through guardrails, and engineer precise prompts for behavior control. Students will also learn to orchestrate advanced multi-agent architectures that handle complex task decomposition and seamless hand-offs. Designed for software engineers, data scientists, and technical architects, this concise program ensures you can build, secure, debug, and deploy production-ready AI agents to the cloud in just a few hours.
About the creator
Sundog Education by Frank Kane
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Frank Kane is the founder of Sundog Education, an online learning platform dedicated to making highly technical concepts accessible to developers worldwide. With a rich background that includes over nine years as a senior engineer and manager at Amazon and IMDb, Frank brings real-world industry expertise directly into his curriculum. Over his career, he has designed and managed massive distributed systems, a foundation that informs his popular courses on System Design and Cloud Computing. As technology has shifted, Frank has transitioned his focus to modern artificial intelligence, machine learning, and generative AI frameworks. He specializes in translating cutting-edge developments, such…Show more
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Program Overview
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Learning format
Subcategory
Price
Price may change · updated within 1–2 weeks
Course language
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
Best For
- Software developers looking to transition from static LLM prompting to autonomous agent systems
- Data scientists who want to integrate RAG and vector databases into production-ready AI workflows
- Technical professionals eager to learn industry-standard orchestration techniques for multi-agent architectures
- Python programmers seeking a hands-on, fast-paced guide to the OpenAI SDK
Not For
- Complete beginners with zero prior experience in Python programming or software development
- Learners looking for a high-level conceptual overview without hands-on coding or implementation
- Experts searching for advanced theoretical research on complex neural network architectures
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