Uploaded March 2026 | Updated September 2026, 2 weeks ago
Learn how enterprise teams move from data profiling and feature engineering through automated machine learning, explainability, and production deployment — all within a single, coordinated platform.
Rather than stitching together disconnected tools, H2O.ai is designed to support the full journey from experimentation to operations with shared governance, security controls, and lifecycle management built in. The course also covers how traditional predictive modeling connects with modern generative AI capabilities and agent-driven workflows.
What You Will Learn :
✦ Data Preparation & Feature Engineering: Automated profiling, transformations, and feature pipelines from raw data to model-ready inputs.
✦ Automated Machine Learning: Model training, explainability, and bias testing with H2O Driverless AI.
✦ MLOps & Production Deployment: Model registration, real-time serving, drift monitoring, and lifecycle management.
✦ Generative AI & Agentic Workflows: Connecting predictive models with LLMs and autonomous agents via Enterprise h2oGPTe.
✦ Enterprise Governance: Unified security controls, audit logging, and compliance across the entire AI lifecycle.
🔗 H2O.ai Platform Overview: h2o.ai
🎓 H2O.ai University: h2o.ai/university
📚 H2O.ai Documentation: docs.h2o.ai
Learn how enterprise teams move from data profiling and feature engineering through automated machine learning, explainability, and production deployment — all within a single, coordinated platform.
Rather than stitching together disconnected tools, H2O.ai is designed to support the full journey from experimentation to operations with shared governance, security controls, and lifecycle management built in. The course also covers how traditional predictive modeling connects with modern generative AI capabilities and agent-driven workflows.
What You Will Learn :
✦ Data Preparation & Feature Engineering: Automated profiling, transformations, and feature pipelines from raw data to model-ready inputs.
✦ Automated Machine Learning: Model training, explainability, and bias testing with H2O Driverless AI.
✦ MLOps & Production Deployment: Model registration, real-time serving, drift monitoring, and lifecycle management.
✦ Generative AI & Agentic Workflows: Connecting predictive models with LLMs and autonomous agents via Enterprise h2oGPTe.
✦ Enterprise Governance: Unified security controls, audit logging, and compliance across the entire AI lifecycle.
🔗 H2O.ai Platform Overview: h2o.ai
🎓 H2O.ai University: h2o.ai/university
📚 H2O.ai Documentation: docs.h2o.ai
