Azure Mastery

Microsoft Certification AI-200

Predict your score. Pass with proof.

On-device AI scores your readiness, builds an adaptive study plan, and flags topics fading from memory — before they cost you the exam.

444 practice questions AI score prediction 100% offline
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AI-200 Practice Questions & Exam Prep — Microsoft AI Cloud Developer

Get exam-ready for AI-200 (Microsoft AI Cloud Developer) on iPhone or iPad. Azure Mastery uses on-device AI to predict your readiness score across all five AI-200 domains, build a personalised study plan from your weak spots, and surface topics you're forgetting. Core study stays on-device and works offline; optional sync uses your private iCloud account.

The exam

What is the AI-200 exam?

AI-200 is the Microsoft Certified: AI Cloud Developer Associate exam — the credential hiring managers expect when posting "AI Cloud Developer", "AI Platform Engineer", or "Vector Database Developer" roles. AI-200 covers building AI-powered cloud solutions on Azure: compute, vector storage, integration pipelines, security and identity for AI workloads, and operational monitoring.

AI-200 is hands-on and infrastructure-aware. It validates that you can develop AI-powered compute solutions (Azure Functions, Container Apps, AKS for AI workloads), develop for vector-enabled storage and data (Azure Cosmos DB vector search, Azure SQL vector capabilities, Azure AI Search vector indexes), implement AI pipelines and integration (Azure Data Factory, Logic Apps, event-driven patterns), implement security and identity for AI (managed identities, Microsoft Entra, Private Link, content filters), and monitor and optimise AI solutions (Application Insights, cost controls, performance tuning). Expect scenario questions that combine compute, data, and identity choices.

Microsoft updated the AI-200 skills outline in March 2026. Every question in Azure Mastery's AI-200 bank is mapped to the current outline — no leftover questions on retired services. Read the official outline at learn.microsoft.com.

Skills measured · April 2026

AI-200 exam objectives

Five domains, with weights set by Microsoft's March 2026 update. Every domain summary below is paraphrased from the official skills outline; bullet-level objectives in Azure Mastery are tagged so you always know which domain you're being tested on and where your weak spots cluster.

Aura presents a visual map of data, models, agents, and responsible AI skills.
AI & agent skill map

Develop AI-powered compute solutions20–25%

Explore key topics

Tied for the largest domain. Choose and configure compute hosts for AI workloads: Azure Functions (Premium / Flex Consumption for AI calls), Azure Container Apps (jobs, scale-to-zero), Azure Kubernetes Service (GPU node pools, KAITO, Ray clusters), and serverless GPUs. Plus Azure Container Registry, container image best practices for AI, autoscaling strategies, and cold-start mitigation. Around 8–15 questions per sitting.

Develop for vector-enabled storage and data15–20%

Explore key topics

The vector-database surface. Azure Cosmos DB for NoSQL, MongoDB vCore, and PostgreSQL — native vector indexes, similarity search (cosine, dot product, Euclidean), hybrid filtering. Azure SQL vector capabilities. Azure AI Search vector indexes vs hybrid search vs semantic ranking. Embedding generation strategies and chunking. Around 6–12 questions.

Implement AI pipelines and integration20–25%

Explore key topics

Tied for the largest domain. Azure Data Factory and Synapse pipelines for batch AI workflows, Logic Apps and Power Automate for event-driven AI integration, Azure Functions with Event Grid / Service Bus / Storage Queue triggers. Plus retry and idempotency patterns, async vs sync invocation of AI services, structured-output parsing. Around 8–15 questions.

Implement security and identity for AI15–20%

Explore key topics

Managed identities for AI service access, Microsoft Entra app registrations and consent, Private Link / Private Endpoints for AI services, customer-managed keys, content filters and abuse monitoring on Azure OpenAI, secrets management via Azure Key Vault, role-based access for Foundry projects. Around 6–12 questions.

Monitor and optimize AI solutions10–15%

Explore key topics

Smallest domain. Application Insights instrumentation for AI calls, custom telemetry for token usage and latency, distributed tracing across AI pipelines, cost dashboards, performance tuning (caching, batching, model selection), and capacity planning for token throughput. Around 4–9 questions.

Designed for AI-200

How Azure Mastery helps you pass AI-200

Azure Mastery ships with 444 AI-200 practice questions, every one written specifically against the current (March 2026) skills outline. Each question carries a domain tag mapped to the official five domains (compute, vector storage, pipelines, security, monitor/optimize), so you always know which area you're being tested on and where your weak spots are clustered. Vector-index configs, Bicep deployment templates for AI services, and event-driven pipeline scenarios appear throughout — matching the format of the live exam.

The on-device Exam IQ engine predicts your AI-200 score before you sit the exam. After roughly 30 questions it has enough signal to give a confidence-scored prediction (e.g. "786 ±37, 68% confidence") — and tells you the specific topics that are dragging your readiness down. No vague "study more" advice; just a ranked list of objectives where improvement would move your score the furthest.

The adaptive study plan rebuilds itself from your answer history. Get a scenario question wrong? The engine surfaces another question in the same domain in your next session. Master a topic across three sessions and it backs off, prioritising the next-highest-leverage gap. The plan optimises for the gap between where you are and the 700 pass score, not for blind volume.

Knowledge decay tracking matters more for AI-200 than for foundational exams — five domains is a lot to retain, and the topic you mastered three weeks into your study window is the topic you'll forget by exam day if you stop revising. Azure Mastery tracks every topic's decay curve and flags topics approaching expiry. The padlock icon on the Today screen is your "revisit before you forget" cue, and weak-spot drills automatically pull from decayed topics first.

Real exam simulation mode runs at AI-200's actual length and time pressure: a randomised 40–60-question set drawn from the full 444-question bank, weighted by domain percentages from the April 2026 outline, with the 100-minute timer running and no jumping back to flag-and-review. It's the closest you can get to the live Pearson VUE / online-proctored experience without sitting the exam.

Answer Coach turns each missed answer into a private, grounded lesson: the misconception, key distinction, and rule to remember. It always uses authored certification guidance; on supported devices, an optional on-device model may rewrite the note only when it passes grounding checks.

During your first week, Aura adapts the next step as you go. Every session ends with a concise recap of what changed, what to focus on, and the best follow-up.

Everything essential runs on-device. Your answer history, readiness gauge, and coaching stay private. Optional sync uses your private iCloud account; there is no Azure Mastery account, tracking, or external processing server.

6-week study plan

Suggested AI-200 study plan

Most candidates pass AI-200 after four to eight weeks of focused study, depending on prior Azure experience. The six-week plan below maps onto the five AI-200 domains, Azure Mastery's adaptive sessions, and the in-app exam simulator. Adjust pace to taste — the readiness gauge tells you when you're done, not the calendar.

  1. Compute and vector storage

    • Week 1: Develop AI-powered compute solutions — Azure Functions, Container Apps, AKS GPU pools, ACR, autoscaling, cold-start mitigation.
    • Week 2: Develop for vector-enabled storage and data — Azure Cosmos DB vector indexes, Azure SQL vector capabilities, Azure AI Search vector vs hybrid search, embedding generation and chunking strategies.
  2. Pipelines and security

    • Week 3: Implement AI pipelines and integration — Azure Data Factory, Synapse pipelines, Logic Apps, Power Automate, Azure Functions with event triggers, retry and idempotency patterns.
    • Week 4: Implement security and identity for AI — managed identities, Microsoft Entra app registrations, Private Link, customer-managed keys, content filters, Azure Key Vault, RBAC for Foundry projects.
  3. Monitor, optimise, sharpen, simulate

    • Week 5: Monitor and optimize AI solutions — Application Insights for AI calls, custom telemetry for tokens and latency, distributed tracing, cost dashboards, caching and batching strategies, capacity planning.
    • Week 6: Run Focus Weak Spots every morning, then two end-to-end Exam Simulator runs at full 100-minute length. Schedule the exam when readiness gauge is 750+ with reasonable confidence.

Inside the app

Every Microsoft question type, on iPhone

AI-200's question bank uses the same formats Microsoft puts on the live exam — not just multiple choice. Each visualisation below is a faithful mock of how the type renders inside Azure Mastery on iPhone and iPad. Exam-simulator mode runs all of them at full 100-minute length with no flag-and-review jumps, mirroring Pearson VUE.

Multiple choice

A real AI-200 question-bank example with one correct answer. The app explains every option after you answer.

Exam-specific sample

Multi-select

A real AI-200 multi-select item. Every required selection must be correct to earn the mark.

All-or-nothing

Drag-and-drop

A real AI-200 interactive-format prompt, rendered for touch on iPhone and iPad.

Interactive item

Hotspot

A real AI-200 prompt that tests recognition inside a visual or contextual interface.

Tap target

Case studies

A real AI-200 case-study scenario with linked questions that share the same requirements and environment.

Multi-question

Answer Coach

Answer Coach uses the bank's authored rationale to explain the misconception, key distinction, and rule to remember. On supported devices, an optional on-device model may rewrite the note only when it passes grounding checks.

App exclusive

Frequently asked

AI-200 FAQs

How much does the AI-200 exam cost?

The AI-200 voucher is USD $165 in the United States. Pricing varies by region — in the UK it's typically around £128. Microsoft sometimes runs free-voucher promotions during events such as Microsoft Build or Microsoft Ignite, so check your Microsoft Learn profile for any active offers before booking. AI-200 also requires annual renewal (free, online), so factor that into long-term cost planning.

Does the AI-200 certification expire?

Yes. Microsoft Associate certifications including AI-200 expire annually. Renewal is free — a 25–30 question online assessment on Microsoft Learn within the six-month window before your expiration date. The renewal targets recent skills outline updates, so staying current is straightforward if you remain broadly active in the role. (Fundamentals certifications such as AZ-900 are different — those don't expire.)

What is the AI-200 retake policy if I fail?

The first retake is allowed after 24 hours. Second and third retakes each require a 14-day wait. Microsoft caps retakes at five attempts per 12-month rolling period. Each attempt requires a new voucher purchase.

How long should I study for AI-200?

Allow four to eight weeks of focused study if you already develop on Azure. Spend longer if Python, Azure SDKs, containerized applications, messaging, vector databases, identity, monitoring, or troubleshooting are new to you. Azure Mastery's readiness gauge helps you decide when to schedule the exam.

AI-200 vs AI-103 — different roles?

Different emphases. AI-200 validates back-end Azure development for AI solutions, including containers, data services, messaging, identity, monitoring, and troubleshooting. AI-103 focuses on developing AI apps and agents with Python and Microsoft Foundry. AI-200 is cloud-platform and service integration; AI-103 is model, agent, retrieval, and AI-application implementation.

AI-200 vs AI-300 — which next?

AI-200 first. AI-200 is the AI Cloud Developer Associate cert — building the platform that AI workloads run on. AI-300 is the ML Operations Engineer Associate cert — running and operating ML and generative-AI systems in production (MLOps and GenAIOps). AI-200 is upstream of AI-300 in most roles. Take AI-200 to build the platform, AI-300 to operate models and pipelines on top of it.

Where AI-200 fits

Certification paths that include AI-200

AI-200 is the Microsoft Azure AI Cloud Developer Associate cert — the back-end Azure development counterpart to AI-103. It follows AI-901 as the current fundamentals route and pairs naturally with AI-300 for engineers who also operate models and generative AI systems.

Ready to pass AI-200?

Download Azure Mastery free. 444 AI-200 practice questions across all five domains, AI score prediction, full-length exam simulator, adaptive study plan. iPhone & iPad.

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