H2O AI Agents: From Theory to Practice guides you through how AI agents work - combining LLMs, tools, and memory to build autonomous systems using Enterprise h2oGPTe.

This course takes you from foundational concepts to hands-on applications across finance, healthcare, policy development, and energy optimization.

Through practical demonstrations and real-world examples, you'll learn how to create AI agents that summarize, plan, automate, and reason—transforming complex workflows into powerful, production-ready solutions.

 

What you'll learn

  • Introduction to AI Agents
    Learn how AI agents work using LLMs, tools, and memory—powered by h2oGPTe.
  • From Generative to Predictive
    Explore how h2oGPTe blends generative and predictive AI for intelligent automation.
  • Real-World Use Cases
    See how agents are applied across finance, healthcare, energy, and more.
  • Building Autonomous Workflows
    Design agents that can plan, summarize, and automate complex tasks.

  • Deployment & Guardrails
    Understand best practices for deploying safe, reliable agentic systems.
  • Hands-on with h2oGPTe
    Get practical experience building and testing AI agents inside Enterprise h2oGPTe.
H2oGPTe Certified Badge - 2 H2oGPTe Certified Badge - 2

Course Playlist on YouTube

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Additional Course Resources & Access Links

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Julian Garratt, Machine Learning Engineer

Julian is a Machine Learning Engineer at H2O.ai based in Sydney, Australia. He received his Bachelor's degree from the University of New South Wales in Data Science and Decisions, and now focuses on building Agentic AI solutions for Australian clients. Beyond developing technical solutions, he's passionate about responsible AI - particularly in the fairness and transparency of Generative AI models - and runs seminars for both clients and the broader AI community in Sydney. Looking ahead, Julian aims to bridge the gap between cutting-edge AI research and practical business applications, helping Australian organisations ethically implement agentic systems that augment rather than replace human decision-making.