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Microsoft Certification AI-102

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AI-102 Study App for iOS — Microsoft Azure AI Engineer

Get exam-ready for AI-102 (Microsoft Azure AI Engineer) on iPhone or iPad. Azure Mastery uses on-device AI to predict your readiness score across all six AI-102 domains, build a personalised study plan from your weak spots, and surface topics you're forgetting — all without sending a single byte off your device.

The exam

What is the AI-102 exam?

AI-102 is the Microsoft Certified: Azure AI Engineer Associate exam — the credential hiring managers expect when posting "AI Engineer", "Cognitive Services Engineer", "Azure OpenAI Developer", or "Applied AI Engineer" roles. AI-102 covers the AI engineer's day-to-day: building applications on top of Azure AI services (Vision, Language, Speech, Document Intelligence) and Azure OpenAI, including agentic workflows. It pairs with AI-900 on entry and is the natural sibling for DP-100 (Data Scientist).

AI-102 is hands-on and code-aware. It validates that you can plan and manage Azure AI solutions (resource provisioning, RBAC, monitoring, deployment), implement generative AI solutions using Azure OpenAI (prompt engineering, RAG, content filters), implement agentic solutions (Azure AI Foundry agents, tool calling), build computer-vision solutions (image analysis, OCR, custom models with AI Vision), implement NLP solutions (Azure AI Language for entity recognition, sentiment, summarisation; Azure AI Speech for transcription and synthesis), and build knowledge-mining and information-extraction solutions (Azure AI Search, Document Intelligence). Expect scenario questions with REST API calls, Python SDK snippets, and config JSON.

Microsoft updated the AI-102 skills outline on 23 December 2025, adding the new "Implement an agentic solution" domain and rebalancing weights toward generative AI. Every question in Azure Mastery's AI-102 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-102 exam objectives

Six domains, with weights set by Microsoft's December 2025 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.

Plan and manage an Azure AI solution20–25%

Tied for the largest domain. Plan and provision Azure AI services resources — multi-service vs single-service accounts, RBAC roles, customer-managed keys, regional and SKU choices. Manage authentication (keys, RBAC, managed identities), networking (VNet integration, private endpoints), and content moderation. Plus Responsible AI considerations, monitoring with Azure Monitor and Application Insights, and deployment strategies (containers, ARM/Bicep). Around 8–15 questions per sitting.

Implement generative AI solutions15–20%

Azure OpenAI end-to-end. Provision Azure OpenAI resources, deploy models, choose the right model (GPT family, embeddings, image, audio), prompt engineering basics (system prompts, few-shot, chain-of-thought), retrieval-augmented generation (RAG) with Azure AI Search and embeddings, content filters and abuse monitoring, fine-tuning workflows, evaluating model outputs (groundedness, relevance, fluency). Around 6–12 questions.

Implement an agentic solution5–10%

New domain in the December 2025 outline — smallest by weight but distinct. Cover Azure AI Foundry agents, tool calling and function definitions, agent grounding via knowledge sources, multi-agent orchestration patterns, agent observability and tracing. Around 2–6 questions.

Implement computer vision solutions10–15%

Azure AI Vision for image analysis (tagging, captioning, OCR via Read API, smart cropping), Custom Vision for image classification and object detection (training, evaluation, deployment), Face service (detection, identification, verification — note Limited Access policy), and Video Analyzer for Media. Around 4–9 questions.

Implement natural language processing solutions15–20%

Azure AI Language for entity recognition, sentiment analysis, key phrase extraction, language detection, summarisation, custom text classification, custom named-entity recognition, conversational language understanding (CLU), and question answering. Azure AI Speech for speech-to-text, text-to-speech, speech translation, custom speech, and pronunciation assessment. Azure AI Translator for text and document translation. Around 6–12 questions.

Implement knowledge mining and information extraction solutions15–20%

Tied for the largest domain in scope. Azure AI Search end-to-end — indexers, indexes, skillsets, semantic search, vector search, hybrid search. Document Intelligence (formerly Form Recognizer) — prebuilt models (invoice, receipt, ID, business card, layout) and custom models (template, neural). Around 6–12 questions.

Designed for AI-102

How Azure Mastery helps you pass AI-102

Azure Mastery ships with 334 AI-102 practice questions, every one written specifically against the current (December 2025) skills outline — not generic AI trivia. Each question carries a domain tag mapped to the official six domains (Plan/manage, generative AI, agentic, vision, NLP, knowledge mining), so you always know which area you're being tested on and where your weak spots are clustered. REST API calls, Python SDK snippets, Azure OpenAI prompt configurations, and Foundry project setups appear throughout — matching the format of the live exam.

The on-device Exam IQ engine predicts your AI-102 score before you sit the exam. After roughly 30 questions it has enough signal to give a confidence-scored prediction (e.g. "708 ±60, 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-102 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-102's actual length and time pressure: a randomised 40–60-question set drawn from the full 334-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.

Everything runs on-device. Your answer history, your readiness gauge, your decay alerts — none of it leaves your iPhone or iPad. No account required to start, no tracking, no sync server. Privacy-first by design.

6-week study plan

Suggested AI-102 study plan

Most candidates pass AI-102 after four to eight weeks of focused study, depending on prior Azure experience. The six-week plan below maps onto the five AI-102 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. Plan, manage, and generative AI

    • Week 1: Plan and manage Azure AI solutions — resource provisioning (multi-service vs single-service), RBAC, customer-managed keys, networking, content moderation, Responsible AI considerations, monitoring, deployment via containers and ARM/Bicep.
    • Week 2: Implement generative AI solutions — Azure OpenAI provisioning, model deployment, prompt engineering (system prompts, few-shot, chain-of-thought), RAG with Azure AI Search and embeddings, content filters, fine-tuning, evaluation metrics.

  2. Vision and NLP

    • Week 3: Computer vision — Azure AI Vision (analysis, OCR via Read API), Custom Vision (classification and object detection), Face service (Limited Access policy), Video Analyzer for Media.
    • Week 4: NLP — Azure AI Language (entity recognition, sentiment, summarisation, CLU, question answering), Azure AI Speech (STT, TTS, translation, custom speech), Azure AI Translator.

  3. Knowledge mining, agentic, sharpen, simulate

    • Week 5: Knowledge mining — Azure AI Search (indexers, indexes, skillsets, semantic and vector search), Document Intelligence (prebuilt and custom models). Plus agentic — Azure AI Foundry agents, tool calling, multi-agent orchestration.
    • 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-102'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

One correct answer from four to six options. The most common type on every Azure exam — practical recall of services, settings, and limits.

~50% of questions

Multi-select

Pick two or more correct answers from a list. Microsoft tells you exactly how many to choose. Partial credit not awarded — you need every selection right.

All-or-nothing

Drag-and-drop

Arrange items into the correct sequence — deployment steps, the order operations occur in a pipeline, troubleshooting flows. Long-press to drag on touch.

Order matters

Hotspot

Tap the correct area of an image — the right setting in a portal screenshot, the right resource in a topology diagram. Practical visual recall under time pressure.

Tap target

Case studies

A multi-paragraph scenario followed by 4–6 linked questions. Common on AI-102 in the storage and identity domains; dominant on AZ-305 and AZ-400.

Multi-question

Why Wrong AI

An Azure Mastery exclusive. When you answer incorrectly, an on-device Apple Foundation Model writes a targeted explanation grounded in the correct rationale. Never leaves your device.

App exclusive

Frequently asked

AI-102 FAQs

How much does the AI-102 exam cost?

The AI-102 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-102 also requires annual renewal (free, online), so factor that into long-term cost planning.

Does the AI-102 certification expire?

Yes. Microsoft Associate certifications including AI-102 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-102 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-102?

Most candidates pass AI-102 after four to eight weeks of focused study, assuming some prior IT or cloud experience. If Azure is genuinely new to you, plan for two to three months — the exam expects you to know specific PowerShell and Azure CLI commands, not just describe concepts. Azure Mastery's readiness gauge tells you when you're at exam-ready; don't book until it shows roughly 720 or higher with reasonable confidence.

AI-102 vs AI-900 — which should I take first?

AI-900 first if you don't already build AI applications professionally. AI-900 (Microsoft Azure AI Fundamentals) teaches the AI vocabulary — workload types, the responsible-AI principles, the Azure AI service catalogue — without expecting code. AI-102 is the role-based Associate exam: it expects hands-on Python or REST API calls against Azure AI services and Azure OpenAI. Most candidates pass AI-900 in a few weeks then spend two to three months on AI-102.

AI-102 vs DP-100 — different AI roles?

Different angles. AI-102 is the AI Engineer Associate cert — building applications that consume Azure AI services (Vision, Language, Speech, OpenAI) via SDK and REST. DP-100 is the Data Scientist Associate cert — building, training, deploying, and optimising ML models using Azure Machine Learning. AI-102 is application-side; DP-100 is modelling-side. Many candidates hold both for end-to-end AI/ML engineering roles.

Where AI-102 fits

Certification paths that include AI-102

AI-102 is the Microsoft Azure AI Engineer Associate cert. It pairs with AI-900 as recommended fundamentals and is the gateway into Microsoft's broader AI engineering specialisations. Tap any linked exam below to see its dedicated study app page.

Ready to pass AI-102?

Download Azure Mastery free. 334 AI-102 practice questions across all six domains, AI score prediction, full-length exam simulator, adaptive study plan. iPhone & iPad.

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