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Microsoft AI-102 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Exam Format: | Drag-and-drop, Case studies, Multiple-choice, Active screen questions |
| Certificate Validity Period: | No expiration; certification remains valid unless Microsoft deprecates it |
| Real Exam Qty: | 40-60 |
| Exam Price: | $165 USD |
| Available Languages: | Chinese (Simplified), Japanese, Korean, English |
| Exam Duration: | 120 minutes |
| Related Certifications: | Microsoft Certified: Azure AI Engineer Associate |
| Passing Score: | 700 (on a scale of 1-1000) |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | In-person at Pearson VUE testing centers or online proctored exam |
| Pre Condition: | Recommended: Understanding of Azure services, REST APIs, C#, Python, or JavaScript. No mandatory prerequisites, but Azure Administrator or Developer background is beneficial. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-102/ |
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | 15-20% | - Implement governance and compliance for AI solutions - Manage AI costs and resource allocation - Select appropriate Azure AI services and technologies - Plan and configure secure AI solutions |
| Topic 2: Implement Computer Vision Solutions | 15-20% | - Implement object detection and image classification - Analyze images using Azure AI Vision - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service - Process video and generate insights |
| Topic 3: Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Topic 4: Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Translate text and speech - Build question answering solutions - Implement speech capabilities using Azure AI Speech - Create conversational AI solutions with Azure AI Bot Service |
| Topic 5: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Design document processing pipelines - Create custom skills for Azure AI Search - Implement Azure AI Search solutions - Implement semantic and vector search |
| Topic 6: Implement Generative AI Solutions | 10-15% | - Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques |
Microsoft Designing and Implementing a Microsoft Azure AI Solution Exam — Your Questions Answered
Three versions of the same study materials, each with its own character: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 425 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
Recommended: Understanding of Azure services, REST APIs, C#, Python, or JavaScript. No mandatory prerequisites, but Azure Administrator or Developer background is beneficial. Since requirements change over time, confirm the latest on the official Microsoft exam page before scheduling.
The official Microsoft Designing and Implementing a Microsoft Azure AI Solution outline defines 6 domains. The leading three are Implement Decision Support Solutions (10-15%), Implement Generative AI Solutions (10-15%), and Implement Computer Vision Solutions (15-20%). The full list is in the topics section above, and Prep4away's 425 practice questions cover each one.
Microsoft recommends these training resources for the Microsoft Designing and Implementing a Microsoft Azure AI Solution exam:
Follow the training with steady self-testing — the 425 practice questions from Prep4away help you apply theory and fill any gaps the training leaves.
The AI-102 exam is a Microsoft certification exam validating the Microsoft Designing and Implementing a Microsoft Azure AI Solution syllabus shown above. It belongs to these credential paths: Microsoft Certified: Azure AI Engineer Associate. Candidates in 2026 prepare for it with Prep4away's 425 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
The Microsoft Designing and Implementing a Microsoft Azure AI Solution exam requires 700 (on a scale of 1-1000) to pass, and registration costs $165 USD. A failed attempt means paying the same fee again — a readiness check with the Prep4away engines before booking is the cheaper option.
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In-person at Pearson VUE testing centers or online proctored exam Register for the Microsoft Designing and Implementing a Microsoft Azure AI Solution exam through these official channels:
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The Microsoft Designing and Implementing a Microsoft Azure AI Solution exam contains 40-60 to complete within 120 minutes. Timed simulation in the Prep4away Desktop Test Engine teaches that rhythm before exam day does.
Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions:
You have a Video Indexer service that is used to provide a search interface over company videos on your company ' s website.
You need to be able to search for videos based on who is present in the video. What should you do?
- A. Create a person model and associate the model to the videos.
- B. Edit the faces in the videos.
- C. Create person objects and provide face images for each object.
- D. Invite the entire staff of the company to Video Indexer.
- E. Upload names to a language model.
Correct Answer: A 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You migrate to a Cognitive Search service that uses a higher tier.
Does this meet the goal?
- A. Yes
- B. No
Correct Answer: A 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
You need to develop an automated call handling system that can respond to callers in their own language. The system will support only French and English.
Which Azure Cognitive Services service should you use to meet each requirement? To answer, drag the appropriate services to the correct requirements. Each service may be used once, more than once, or not at all.
You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:

Explanation:
Detect the incoming language:
Service: Speech to Text
Reasoning: The Speech to Text service can transcribe spoken language into text and includes language identification capabilities, allowing the system to detect whether the caller is speaking French or English.
Respond in the callers ' own language:
Service: Text to Speech
Reasoning: The Text to Speech service can convert text responses into spoken language in the detected language (French or English), enabling the system to respond to callers in their own language.
Ordered Mapping:
Detect the incoming language: Speech to Text
Respond in the callers ' own language: Text to Speech
Box 1: Text Analytics
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
Box 2: Translator
Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST APIs. Translator can be used with any operating system and powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language- related operations.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language-detection
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/translator-overview
You need to develop a solution to provide data to executives. The solution must provide an interactive graphical interface, depict various key performance indicators, and support data exploration by using drill down. What should you use in Microsoft Power Bl?
- A. a report
- B. Microsoft Power Apps
- C. a view
- D. a dataflow
Correct Answer: A 🗳️
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
You train an Azure Custom Vision object detection model to identify a company ' s products by using the Retail domain.
You plan to deploy the model as part of a mobile app for Android phones.
You need to prepare the model for deployment.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Correct Answer:

Explanation:
For deployment to a mobile app (Android), Custom Vision requires a compact domain so the model can be exported and run on-device (e.g., as TensorFlow Lite or ONNX). The model was trained using the Retail domain, which is not an exportable compact domain for object detection. Therefore:
Change the model domain to an exportable Object Detection (compact) domain (e.g., General [compact]).
Retrain the model so weights are learned under the new domain-domain changes require retraining.
Export the model for Android (typically TensorFlow Lite or ONNX) and integrate it into the app.
This sequence prepares the model for on-device mobile deployment with minimal extra development.
References (Microsoft Azure AI Solution)
Custom Vision: Only compact domains support model export for edge/mobile.
Changing a domain requires retraining the iteration.
Exporting object detection models supports TensorFlow/TensorFlow Lite/ONNX formats for Android integration.
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