Last Updated: Oct 13, 2026
No. of Questions: 425 Questions & Answers with Testing Engine
Download Limit: Unlimited
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The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.
In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
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| Section | Objectives |
|---|---|
| Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Analyze text using Azure AI Language - Translate and interpret language using Azure AI services |
| Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Implement custom vision models - Extract information using OCR and form recognition |
| Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Build Azure AI Search solutions - Implement document intelligence solutions |
| Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Select appropriate Azure AI services - Plan solution requirements and architecture |
제품 제작 프로젝트에 이미지를 업로드하는 코드를 개발해야 합니다. 솔루션은 접근성 요구 사항을 충족해야 합니다.
코드는 어떻게 작성해야 하나요? 답변하려면 답변 영역에서 적절한 옵션을 선택하세요.
참고: 정답 하나당 1점입니다.
Correct Answer:

Explanation:
Parameter type: stream
Visual features list: VisualFeatureTypes.Description
Result to use: results.Description.Captions[0]
To generate accessible alt text , you should use the caption produced by Azure Computer Vision's Description feature (it produces a human-readable sentence with a confidence score). Therefore:
The image input should be a stream , because you're uploading images (not just passing URLs) during product creation and AnalyzeImage...Async supports image streams .
Request the Description feature in VisualFeatureTypes so the service returns results.Description.Captions.
Use results.Description.Captions[0] and return the caption text if its confidence is high enough (e.g., > 0.5) to meet the accessibility requirement that all images must have relevant alt text .
Other features (Tags, Objects, Brands) are useful for enrichment but do not directly return natural-language captions suitable for alt text.
Microsoft Azure AI Solution References
Computer Vision (Image Analysis) - Description/Captions and features: Microsoft Docs, Image Analysis - VisualFeatureTypes.Description returns description.captions.
https://learn.microsoft.com/azure/ai-services/computer-vision/concept-image-analysis SDK usage (analyze image from a stream): Microsoft Docs, Analyze an image by using the Computer Vision client library .
https://learn.microsoft.com/azure/ai-services/computer-vision/how-to/call-analyze-image?tabs=version-3-2#analyze-an-image-from-a-stream
예측 유지관리를 수행할 계획입니다.
1년 동안 100대의 산업용 기계에서 IoT 센서 데이터를 수집합니다. 각 기계에는 1분 간격으로 데이터를 생성하는 50개의 센서가 있습니다. 총 5,000개의 시계열 데이터 세트를 보유하게 됩니다.
기계 고장을 예측하려면 각 시계열에서 비정상적인 값을 식별해야 합니다.
어떤 Azure Cognitive Services 서비스를 사용해야 하나요?
Correct Answer: A 🗳️
Explanation: Only visible for TestSimulate members. You can sign-up / login (it's free).
언어 리소스용 Azure Cognitive Service가 포함된 Azure 구독이 있습니다. 언어 서비스의 REST 인터페이스 URL을 확인해야 합니다. Azure Portal에서 어떤 블레이드를 사용해야 할까요?
Correct Answer: C 🗳️
Explanation: Only visible for TestSimulate members. You can sign-up / login (it's free).
식품용 골판지 포장재를 생산하는 공장이 있습니다. 인터넷 연결이 간헐적으로 끊깁니다.
패키지에는 각 제품의 샘플 4개가 포함되어야 합니다.
포장의 결함을 식별하고 결함 위치를 운영자에게 제공하는 Custom Vision 모델을 구축해야 합니다. 이 모델은 각 포장에 네 가지 제품이 모두 들어 있는지 확인해야 합니다.
어떤 프로젝트 유형과 도메인을 사용해야 할까요? 정답을 찾으려면 적절한 옵션을 올바른 대상에 드래그하세요. 각 옵션은 한 번, 여러 번 또는 전혀 사용하지 않을 수 있습니다. 콘텐츠를 보려면 창 사이의 분할 막대를 드래그하거나 스크롤해야 할 수도 있습니다. 참고: 올바른 선택은 1점입니다.
Correct Answer:

Explanation:
Project type: Object detection
Domain: General (compact)
The scenario requires building a Custom Vision model for a factory with intermittent internet connectivity.
The solution must:
Detect defects in packaging
Locate the defects (provide bounding box information)
Ensure each package contains four products
Support offline use due to intermittent connectivity
Step 1 - Determine Project Type
Image Classification: Assigns a label to an image, but cannot locate where objects/defects are in the image.
Object Detection: Identifies what objects are present and their location (via bounding boxes).
Since the requirement is to identify location of defects and count products, the correct choice is Object detection.
Step 2 - Determine Domain
General domain: Standard general-purpose domain, optimized for cloud inference.
General (compact) domain: A lightweight version designed for exporting models to run offline on edge devices (iOS, Android, ONNX, etc.). Perfect for scenarios with intermittent internet connectivity.
Food domain: Specialized for food image classification, not defect detection in packaging.
Logo domain: Specialized for logo recognition, irrelevant here.
Since the requirement includes offline capability, the correct domain is General (compact).
The answer:
Project type: Object detection
Domain: General (compact)
Microsoft References
Custom Vision project types: Classification vs Object detection
Domains in Custom Vision (General, General compact, Food, Logo, etc.)
Exporting compact models for offline use
Search1이라는 Azure Al Search 리소스가 있습니다.
Search1을 사용하여 콘텐츠를 인덱싱하는 App1이라는 앱이 있습니다.
Search1을 사용하여 앱이 송장에서 속성을 인식하고 검색할 수 있도록 App1에 사용자 지정 스킬을 추가해야 합니다.
솔루션에 무엇을 포함해야 합니까?
Correct Answer: B 🗳️
Explanation: Only visible for TestSimulate members. You can sign-up / login (it's free).
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