100+ Free Microsoft AI-300 MLOps Engineer Practice Questions
Pass your Microsoft Certified: Machine Learning Operations Engineer Associate (Exam AI-300) exam on the first try — instant access, no signup required.
Your MLOps team wants the same Bicep deployment to create dev, test, and prod Azure Machine Learning workspaces with environment-specific settings. What is the best approach?
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Key Facts: Microsoft AI-300 MLOps Engineer Exam
$165
Exam Fee (USD)
Microsoft
120 min
Exam Duration
Microsoft
700/1000
Passing Score
Microsoft
40-60
Approx. Questions
Microsoft
Pearson VUE
Exam Provider
Microsoft
June 1, 2026
DP-100 Retirement
Microsoft
As of May 2026, Microsoft lists Exam AI-300 (Operationalizing Machine Learning and Generative AI Solutions) as a role-based associate exam scheduled through Pearson VUE for about $165 USD, with 120 minutes to complete it and a 700-out-of-1000 score required to pass. The largest skill area is Implement machine learning model lifecycle and operations at 25-30%, followed by Design and implement a GenAIOps infrastructure at 20-25%, Design and implement an MLOps infrastructure at 15-20%, Implement generative AI quality assurance and observability at 10-15%, and Optimize generative AI systems and model performance at 10-15%. AI-300 replaces DP-100, which retires June 1, 2026.
Sample Microsoft AI-300 MLOps Engineer Practice Questions
Try these sample questions to test your Microsoft AI-300 MLOps Engineer exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.
1In Azure Machine Learning, what is the top-level resource that groups experiments, models, endpoints, datastores, and compute together?
2Which Azure Machine Learning asset abstracts a connection to an Azure storage account so jobs can access data without embedding credentials in code?
3What is the main advantage of an Azure Machine Learning compute cluster over a single compute instance for training jobs?
4You want jobs in your Azure Machine Learning workspace to access a storage account and Key Vault without storing secrets. Which identity approach should you configure?
5Which Azure Machine Learning asset captures the software dependencies, base image, and Python packages needed to run a job reproducibly?
6What is the primary purpose of a reusable component in an Azure Machine Learning pipeline?
7Your organization needs to share curated models and components across multiple Azure Machine Learning workspaces. Which feature should you use?
8Which infrastructure-as-code approach does the AI-300 audience profile expect for deploying Azure Machine Learning workspaces and resources?
9You want to automatically provision Azure Machine Learning resources whenever code is merged to the main branch of your repository. Which tool fits the AI-300 IaC workflow?
10To prevent public internet access to an Azure Machine Learning workspace and keep traffic on your virtual network, what should you configure?
About the Microsoft AI-300 MLOps Engineer Exam
Microsoft's AI-300 exam validates a Machine Learning Operations Engineer who builds and operates MLOps and GenAIOps (together, AIOps) infrastructure on Azure. The blueprint spans Azure Machine Learning workspaces and pipelines, MLflow tracking, managed online and batch endpoints, data drift monitoring, Microsoft Foundry foundation-model deployment, prompt versioning, generative AI evaluation and observability, and RAG and fine-tuning optimization. AI-300 replaces the retiring DP-100 exam.
Questions
50 scored questions
Time Limit
120 minutes
Passing Score
700/1000
Exam Fee
$165 (Microsoft)
Microsoft AI-300 MLOps Engineer Exam Content Outline
Design and implement an MLOps infrastructure
Create and manage Azure Machine Learning workspaces, datastores, and compute targets; build data assets, environments, and components; and implement IaC with Bicep, Azure CLI, GitHub integration, and GitHub Actions while restricting network access.
Implement machine learning model lifecycle and operations
Orchestrate training with MLflow experiment tracking, AutoML, hyperparameter sweeps, and pipelines; register and version MLflow models with responsible AI evaluation; deploy real-time and batch endpoints with safe rollout; and detect data drift with retraining triggers.
Design and implement a GenAIOps infrastructure
Configure Microsoft Foundry resources, projects, managed identities, RBAC, and private networking; deploy foundation models via serverless API endpoints, managed compute, and provisioned throughput; and version and compare prompts using Git repositories.
Implement generative AI quality assurance and observability
Create test datasets and data mapping; apply AI quality metrics including groundedness, relevance, coherence, and fluency; configure risk and safety evaluations; and monitor latency, throughput, token cost, logging, and tracing in Foundry.
Optimize generative AI systems and model performance
Tune RAG retrieval through chunk size, similarity thresholds, and hybrid semantic plus keyword search; select and fine-tune embedding models; and apply advanced fine-tuning with synthetic data, then promote fine-tuned models to production.
How to Pass the Microsoft AI-300 MLOps Engineer Exam
What You Need to Know
- Passing score: 700/1000
- Exam length: 50 questions
- Time limit: 120 minutes
- Exam fee: $165
Keys to Passing
- Complete 500+ practice questions
- Score 80%+ consistently before scheduling
- Focus on highest-weighted sections
- Use our AI tutor for tough concepts
Microsoft AI-300 MLOps Engineer Study Tips from Top Performers
Frequently Asked Questions
What are the official exam facts for Microsoft AI-300?
AI-300 is a role-based associate exam scheduled through Pearson VUE for about $165 USD. You have 120 minutes to complete it, and a scaled score of 700 out of 1000 is required to pass. Microsoft typically presents 40 to 60 questions, including possible case studies and interactive items.
Does AI-300 replace DP-100?
Yes. AI-300, Operationalizing Machine Learning and Generative AI Solutions, is the successor to the Azure Data Scientist Associate exam DP-100, which Microsoft retires on June 1, 2026. AI-300 adds substantial generative AI operations content that DP-100 did not cover.
What skills are weighted most heavily on AI-300?
Implement machine learning model lifecycle and operations is the largest area at 25-30%. Design and implement a GenAIOps infrastructure is 20-25%, Design and implement an MLOps infrastructure is 15-20%, and the two generative AI quality and optimization areas are each 10-15%.
Which Azure services does AI-300 focus on?
The exam centers on Azure Machine Learning for traditional MLOps and Microsoft Foundry for generative AI operations. You should know MLflow, managed online and batch endpoints, data drift monitoring, GitHub Actions, Bicep, prompt flow, evaluations, and retrieval-augmented generation.
How long does the AI-300 certification stay valid?
Microsoft associate certifications expire one year after you earn them. You renew for free by passing a short online assessment on Microsoft Learn during the six months before the expiration date.
What is the best way to prepare for AI-300?
Get hands-on with Azure Machine Learning and Microsoft Foundry, then drill mixed practice questions across all five skill areas. Because model lifecycle and operations carries the most weight, spend the largest share of study time on MLflow tracking, endpoints, and drift monitoring.