Operationalizing Machine Learning and Generative AI Solutions
Practice questions and flashcards for the AI-300 exam (replacing DP-100). Covers MLOps infrastructure with Azure Machine Learning, ML model lifecycle (MLflow, AutoML, endpoints, drift detection), GenAIOps with Microsoft Foundry, generative AI quality assurance (groundedness, coherence, safety evaluations), and optimizing RAG and fine-tuning.
An administrator needs to list all RBAC role assignments for a specific Azure AI Foundry hub resource. Which Azure CLI command should they use?
| Domain | Weight | Items | Coverage |
|---|---|---|---|
Design and implement an MLOps infrastructure | 18% | 75 items | |
Implement machine learning model lifecycle and operations | 28% | 115 items | |
Design and implement a GenAIOps infrastructure | 23% | 100 items | |
Implement generative AI quality assurance and observability | 13% | 80 items | |
Optimize generative AI systems and model performance | 13% | 80 items |
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