AI-300 MLOps Engineer Practice Tests

Prepare for the Microsoft AI-300 exam, Operationalizing Machine Learning and Generative AI Solutions, with six full-length AI-300 practice tests and 360 original, scenario-based questions. The AI-300 exam leads to the Microsoft Certified: Machine Learning Operations Engineer Associate certification and replaces DP-100.

WHAT YOU GET IN THESE AI-300 PRACTICE TESTS

- 6 practice tests x 60 questions = 360 original questions

- The same domain split in every test (11 / 17 / 14 / 9 / 9 questions), kept within the official AI-300 weighting ranges

- A progression from foundational scenarios (tests 1-2), to applied troubleshooting and trade-off questions (tests 3-4), to multi-step expert scenarios (tests 5-6)

- An explanation for every answer option plus an overall explanation, so you learn why each wrong answer is wrong

- Single-answer and multiple-selection questions

AI-300 EXAM SKILLS COVERED (official domains and weighting ranges)

1. Design and implement an MLOps infrastructure (15-20%): Azure Machine Learning workspaces, datastores and authentication, compute, environments, components, registries, Bicep and Azure CLI infrastructure as code, GitHub Actions, managed virtual networks, workspace soft delete

2. Implement machine learning model lifecycle and operations (25-30%): AutoML, hyperparameter sweep jobs, pipelines, distributed training, MLflow models and stages, managed online and batch endpoints, blue-green safe rollout, model monitoring and data drift

3. Design and implement a GenAIOps infrastructure (20-25%): Microsoft Foundry (formerly Azure AI Foundry) resources, projects and RBAC, managed identity, provisioned throughput versus serverless deployment, guardrails and Prompt Shields, prompt versioning with Git

4. Implement generative AI quality assurance and observability (10-15%): built-in and custom evaluators, groundedness, evaluation levels, simulators and synthetic test data, red teaming, tracing, continuous evaluation and alerts

5. Optimize generative AI systems and model performance (10-15%): RAG with hybrid search, chunking, semantic ranking and metadata filtering, embedding model selection, fine-tuning, hyperparameters, synthetic data, fine-tuned model lifecycle

WHO SHOULD TAKE THESE AI-300 PRACTICE EXAMS

- Data scientists and ML engineers preparing for the AI-300 certification, including those coming from DP-100

- DevOps and platform engineers who run machine learning and generative AI workloads on Azure

- Anyone who wants scenario-based practice across MLOps, GenAIOps, evaluation and optimization

HOW TO USE THE TESTS

1. Take the tests in order and read the explanation for every option, including the ones you got right

2. Note which domain you miss most and revisit that section of the official AI-300 study guide on Microsoft Learn

3. Retake a test after a gap, once you can explain why each wrong option is wrong

FREQUENTLY ASKED QUESTIONS

Are these real AI-300 exam questions? No. Every question is original and written for this course. None are taken from the real exam.

Do these practice tests replace DP-100 material? They target the AI-300 skills outline, which emphasizes MLOps and GenAIOps, not the retired DP-100 outline.

Do the tests include labs or case studies? No. The real exam may include performance-based labs and other formats that practice tests cannot reproduce.

Will these tests guarantee that I pass AI-300? No. They are practice material to find and close gaps, not a guarantee.

PLEASE NOTE

- This course is independent. It is not affiliated with, endorsed by, or sponsored by Microsoft. Microsoft, Azure and Microsoft Foundry are trademarks of Microsoft.

- Exam skills outlines and product features change. Compare this course with the current AI-300 study guide on Microsoft Learn. Questions were written against Microsoft Learn documentation as it stood in October 2026, and a few topics involve features documented as preview at that time.