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.
| Domain | Weight | Items | Coverage |
|---|---|---|---|
Implement machine learning model lifecycle and operations | 30% | 150 items | |
Design and implement a GenAIOps infrastructure | 25% | 100 items | |
Design and implement an MLOps infrastructure | 20% | 75 items | |
Implement generative AI quality assurance and observability | 15% | 75 items | |
Optimize generative AI systems and model performance | 10% | 50 items |
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Correct answer: Storage Account, Key Vault, and Application Insights. This is one of 514 practice questions in the AI-300 AI-300: Operationalizing Machine Learning and Generative AI Solutions pack on ReadRoost.
The AI-300 AI-300: Operationalizing Machine Learning and Generative AI Solutions study pack on ReadRoost includes 514 practice questions and 322 flashcards, covering 5 exam domains including Implement machine learning model lifecycle and operations. Every question has a detailed explanation so you understand why each answer is right or wrong.
Yes. The AI-300 AI-300: Operationalizing Machine Learning and Generative AI Solutions pack is mapped to the latest official exam objectives and is maintained by the ReadRoost team. You get flashcards with spaced repetition, timed practice exams, and AI-powered explanations.
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A company provisions a new Azure Machine Learning workspace. Which three Azure resources are automatically created as dependent resources to support core functionality?