AI-300
Exam AI-300: Operationalizing Machine Learning and Generative AI Solutions
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ExploreAbout this exam
Exam AI-300 is the requirement for the Microsoft Certified: Machine Learning Operations Engineer Associate credential. It targets engineers who build and operate AI workloads on Azure across two tracks: classic MLOps using Azure Machine Learning, and GenAIOps using Microsoft Foundry. Microsoft expects candidates to have a data science background with Python, entry-level DevOps familiarity (GitHub Actions, command-line interfaces), and hands-on experience with infrastructure as code using Bicep and Azure CLI. The exam measures five areas: designing and implementing MLOps infrastructure (15–20%), machine learning model lifecycle and operations (25–30%), GenAIOps infrastructure (20–25%), generative AI quality assurance and observability (10–15%), and optimizing generative AI systems and model performance (10–15%). A score of 700 or greater is required to pass, and the certification expires annually unless renewed through a free online assessment on Microsoft Learn. Preparation should be hands-on: provision workspaces and Foundry resources, build training pipelines, deploy and monitor endpoints, and run evaluations yourself, alongside Microsoft's self-paced learning paths, documentation, and the practice assessment offered through AI Skills Navigator. This page is an independent study resource and is not affiliated with or endorsed by Microsoft.
What you'll study
About AI-300 preparation
What score do I need to pass Exam AI-300?
Microsoft states that a score of 700 or greater is required to pass. Your score report breaks results down by skill area, which makes it useful for spotting which domain pulled you down before a retake.
How long is the certification valid, and how do I renew it?
Microsoft associate, expert, and specialty certifications expire annually. Renewal is done by passing a free online assessment on Microsoft Learn rather than by re-sitting the full exam. Put a calendar reminder ahead of the anniversary date so the credential does not lapse.
How much does each domain count toward the score?
The study guide publishes ranges only: MLOps infrastructure 15–20%, model lifecycle and operations 25–30%, GenAIOps infrastructure 20–25%, generative AI quality assurance and observability 10–15%, and optimization of generative AI systems and model performance 10–15%. The lifecycle domain is the single largest block.
How many questions are on the exam and how long do I have?
Neither is stated in the published study guide, so treat any specific number you see elsewhere with suspicion. The exam sandbox lets you explore the environment beforehand so navigation and item types are not a surprise on the day.
What question formats should I expect?
The study guide does not enumerate item formats. It does note that most questions cover generally available features, though questions on Preview features may appear when those features are commonly used. Build breadth across Azure Machine Learning and Foundry rather than memorizing one interface.
In what order should I study the domains?
Follow the weights. Start with model lifecycle and operations (25–30%), then GenAIOps infrastructure (20–25%), then MLOps infrastructure (15–20%). Add quality assurance and optimization last, since evaluation and RAG tuning assume you already understand deployments, endpoints, and monitoring.
What background do I need before starting?
Microsoft describes a data science background with Python programming, an entry-level understanding of DevOps practices such as GitHub Actions and command-line interfaces, and knowledge of MLOps using Machine Learning, Foundry, GitHub Actions, and infrastructure as code with Bicep and Azure CLI.
What are the most common ways candidates fail?
Typical weak spots are shallow coverage of deployment mechanics (real-time versus batch endpoints, progressive rollout, rollback), monitoring and drift detection, and underestimating Foundry-specific work such as provisioned throughput and prompt versioning. Preview features also surprise candidates who only study generally available documentation.
Is the exam available in my language, and can I get extra time?
Localized versions are updated roughly eight weeks after the English version. If the exam is not available in your preferred language, you can request an additional 30 minutes to complete it. Accommodations for assistive devices or extra time can also be requested in advance.
Is there a practice test?
Yes. Microsoft points candidates to the practice assessment on AI Skills Navigator, reachable from the certification page. You must be signed in to AI Skills Navigator to launch it, so set up and verify your account before you sit down to practice.