AI-300
AI-300: Machine Learning Operations Engineer
Everything for Microsoft exam AI-300: format, passing score, the five MLOps and GenAIOps skill areas, a 4-week study plan and free sample questions.
- Duration
- 120 min
- Passing score
- 700 / 1000
- Replaces
- DP-100
- Languages
- English
AI-300, Operationalizing Machine Learning and Generative AI Solutions, is Microsoft’s exam for the engineers who get models into production and keep them there. Passing it earns the Microsoft Certified: Machine Learning Operations Engineer Associate credential.
It replaces DP-100. The Azure Data Scientist Associate certification was retired on June 1, 2026, and Microsoft positions AI-300 as its successor. The emphasis moved from training a good model to running one: infrastructure as code, CI/CD with GitHub Actions, deployment and rollback, drift detection, and the same discipline applied to generative AI in Microsoft Foundry.
Microsoft calls the combination AI operations: MLOps for traditional models in Azure Machine Learning, and GenAIOps for foundation models, prompts, evaluations and agents in Foundry. The exam tests both halves.
What the exam covers
| Skill area | Weight |
|---|---|
| Design and implement an MLOps infrastructure | 15–20% |
| Implement machine learning model lifecycle and operations | 25–30% |
| Design and implement a GenAIOps infrastructure | 20–25% |
| Implement generative AI quality assurance and observability | 10–15% |
| Optimize generative AI systems and model performance | 10–15% |
The model lifecycle domain is the largest, and it is the one closest to DP-100. The three generative AI domains together are worth 40–55%, which is where most former DP-100 candidates have the most to learn.
Where to start
Read the exam format for the mechanics, then what changed from DP-100 if you studied for the old exam. The study plan fits in four weeks if you already train models in Azure Machine Learning.
AI-300 guides
- AI-300 exam format: questions, score and costThe AI-300 format: 120 minutes, passing score 700, English only, question types, pricing, and what the five MLOps and GenAIOps weights mean.
- AI-300 vs DP-100: what changed?DP-100 retired on 1 June 2026 and AI-300 replaced it. What carries over from the data scientist exam, what was dropped, and the new GenAIOps content.
- AI-300 study plan: pass in 4 weeksA four-week AI-300 study plan: IaC and workspaces, the model lifecycle, Foundry GenAIOps, then evaluation and RAG tuning, with a hands-on lab each week.
- Free AI-300 sample questions with answersFive free AI-300 practice questions on GitHub Actions, endpoint rollout, drift, Foundry deployments and groundedness, each with an explained answer.
- AI-300 MLOps infrastructure explainedThe AI-300 MLOps infrastructure domain: Azure Machine Learning workspaces, compute, environments, registries, Bicep, GitHub Actions and network isolation.
- AI-300 ML model lifecycle explainedThe largest AI-300 domain: MLflow tracking, sweeps, pipelines, model registration, online and batch endpoints, safe rollout and drift monitoring.
- AI-300 GenAIOps infrastructure explainedThe AI-300 GenAIOps domain: Foundry resources and projects, identity and private networking, model deployment types, PTUs and prompts versioned in Git.
- AI-300 GenAI quality and observabilityThe AI-300 evaluation and observability domain: test datasets, groundedness and relevance, safety evaluators, tracing and token cost in Foundry.
- AI-300 GenAI optimization: RAG and tuningThe AI-300 optimization domain: chunk size, similarity thresholds, hybrid search, embedding models, fine-tuning methods and synthetic training data.
- Is AI-300 hard? Exam difficulty explainedHow hard AI-300 really is: why its two halves, the DevOps tooling, the generative AI evaluation content and the English-only exam shape the difficulty.
- Is AI-300 worth it? Who should take itIs AI-300 worth taking? Who benefits, what it costs, and why the retirement of DP-100 makes it Microsoft's associate exam for MLOps and GenAIOps work.
- Free AI-300 practice test: 20 questionsA free 20-question AI-300 practice test on Azure Machine Learning, GitHub Actions, endpoints, Foundry, evaluation and RAG, with explained answers.
- AI-300 study resourcesWhat to study for AI-300, which DP-100 material still helps, the official practice assessment, and six labs that cover most of the outline.
- AI-300 cheat sheetA one-page AI-300 reference: the five skill areas, which Azure Machine Learning or Foundry feature answers each requirement, evaluators and common traps.