Generative AI in production requires more than a working model; it demands operational discipline. This course establishes the conceptual and technical foundation for GenAIOps, helping you understand how it differs from traditional MLOps and how to apply it on Azure.

GenAIOps Foundations & Data Operations

GenAIOps Foundations & Data Operations
This course is part of Microsoft Generative AI Operations (GenAIOps) Professional Certificate

Instructor: Microsoft
What you'll learn
Explain the key differences between MLOps and GenAIOps and apply the Microsoft GenAIOps Maturity Model to assess organizational readiness.
Map the GenAIOps operating loop to Azure tools and select appropriate accelerator templates for different solution types.
Design DataOps workflows for grounding data, including ingestion pipelines, chunking strategy versioning, and index maintenance.
Implement data freshness SLAs, right-to-be-forgotten controls, and grounding content validity audits for compliance requirements.
Skills you'll gain
- MLOps (Machine Learning Operations)
- Solution Architecture
- Technology Roadmaps
- Data Quality
- Retrieval-Augmented Generation
- Data Analysis
- Model Evaluation
- Embeddings
- Cloud Computing
- Data Maintenance
- Data Validation
- Data Pipelines
- Continuous Monitoring
- Information Technology
- Data Governance
- Data Science
- Enterprise Architecture
Tools you'll learn
Details to know

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September 2026
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