Andreea is a data scientist with over 7 years of experience in demystifying AI and Data Science concepts for anyone keen on working in this exciting field using cutting-edge technology. Having obtained a Master’s Degree in Quantitative Economics and Econometrics from Lumière Lyon 2 University, she enjoys integrating machine learning principles with real-world applications. Andreea’s passion lies in developing engaging training programs and ensuring an optimal customer education journey. As she frequently likes to remark, “AI is essentially Economics turbocharged by data, with a sprinkle of innovation.”
Getting Started with H2O AI Managed Cloud
- H2O AI Managed Cloud
- H2O MLOps
- Enterprise h2oGPTe
- H2O Driverless AI
- H2O Cascade
- H2O Document AI
- Last updated 08/2026
- English
- Beginner
- 22m · 6 lessons
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About this course
This course introduces H2O AI Managed Cloud, a fully managed, isolated AI environment where data preparation, model development, and deployment all run in one place, with the infrastructure handled for you.
You will learn about what you can build across predictive AI and generative AI, how to activate your account through an External Okta account, and how to find your way around the platform from your first login.
In addition, you will learn and see where H2O MLOps, Enterprise h2oGPTe, and H2O Document AI sit inside your environment, and get an administrator's view of users, AI Unit reporting, and platform-wide access.
What you'll learn
Skills you will take away
Platform Fundamentals
Understand what a managed, isolated AI environment provides, and how it connects data to production.
Predictive AI & Generative AI
See how both approaches run on one platform, from fraud detection to retrieval-augmented generation.
Account Activation & Access
Complete the full setup path through an External Okta account, including password and multi-factor authentication.
Interface Navigation
Find your way around the homepage, App Store, AI Engines, Apps, Secrets, Audit Trail, and Workspaces.
Operations & AI for Documents
Locate H2O MLOps, Enterprise h2oGPTe and H2O Document AI inside your own environment.
Platform Administration
Manage users and groups, OAuth clients, AI Unit reporting, analytics, and resource blocking.
Course playlist on YouTube
Open the playlist (opens in a new tab)6 lessons, start to finish
Pick a lesson to play it here. Watch in order, then take the quiz.
H2O.ai Managed Cloud is a fully managed, isolated AI environment where data preparation, model development, and deployment all run in one place. This first lesson covers what the platform is and the problem it solves. Most teams are not short of ideas, they are slowed down by data living in one system, models being built in another, and deployment happening somewhere else. You will also see the two principles behind the setup. Managed means H2O.ai runs the infrastructure for you, including GPU compute when the workload needs it. Isolated means your environment is dedicated, so data, compute, and workloads are never shared with another customer. Covered in this video: The three capabilities the platform brings together: automated machine learning, generative AI, and model operations Why fragmented tooling causes delays, duplicated effort, and gaps in governance Where H2O Driverless AI, H2O LLM Studio, and Enterprise h2oGPTe sit in the platform What managed and isolated mean for security, privacy, and enterprise governance LINKS H2O.ai University: https://h2o.ai/university Documentation: https://docs.h2o.ai Request access or a demo: https://h2o.ai/demo Support: support@h2o.ai ABOUT H2O.ai H2O.ai builds the platform enterprises use to develop, deploy, and operate AI on their own private data, across predictive machine learning and generative AI. #H2Oai #EnterpriseAI #MLOps
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