GenAIOps Foundations & Data Operations

О курсе

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. You'll learn to map the complete GenAIOps operating loop from Define & Explore through Build, Evaluate, Deploy, Monitor, and Feedback to specific Azure tools and team responsibilities. You'll evaluate implementation starting points, including Azure OpenAI SDK-based templates and platform-native toolchain options, and choose the right fit for different solution types. The course then shifts to DataOps: the data management discipline that powers reliable RAG solutions. You'll design grounding data ingestion pipelines, chunking and embedding versioning strategies, vector store index maintenance workflows, and data freshness SLAs. You'll also learn to implement right-to-be-forgotten controls, data lineage tracking, and grounding content validity audit processes for compliance-sensitive environments.

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Microsoft

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