Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate (AI-300)

MLOps and GenAIOps on Azure — CI/CD for ML, model lifecycle automation, and drift monitoring across Azure ML and AI Foundry.

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Skills covered

• Design and implement an MLOps infrastructure on Azure — workspaces, compute, source control, secrets
• Implement machine learning model lifecycle and operations — training pipelines, registries, versioning, CI/CD
• Design and implement a GenAIOps infrastructure — Azure AI Foundry, prompt flow, retrieval-augmented orchestration
• Implement generative AI quality assurance and observability — evaluations, guardrails, content safety, tracing
• Optimize generative AI systems and model performance — cost, latency, prompt tuning, model selection
• Practical use of Azure DevOps / GitHub Actions for automated training and deployment workflows
• Production model monitoring and drift detection for both classical ML and LLM endpoints

Issued

Microsoft — 2026-05-13