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| Section | Weight | Objectives |
|---|---|---|
| Plan and Manage an Azure AI Solution | 15-20% | - Manage AI costs and resource allocation - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement semantic and vector search - Create custom skills for Azure AI Search - Design document processing pipelines - Implement Azure AI Search solutions |
| Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Create conversational AI solutions with Azure AI Bot Service - Analyze text using Azure AI Language - Implement speech capabilities using Azure AI Speech - Translate text and speech |
| Implement Computer Vision Solutions | 15-20% | - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision - Implement object detection and image classification - Process video and generate insights - Implement Azure AI Face service |
| Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Implement Generative AI Solutions | 10-15% | - Use Azure OpenAI Service for generative AI - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques - Apply responsible AI practices |
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NEW QUESTION # 10
You are building a chatbot.
You need to use the Content Moderator service to identify messages that contain sexually explicit language.
Which section in the response from the service will contain the category score, and which category will be assigned to the message? To answer, select the appropriate options in the answer area, NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 11
You have 1,000 scanned images of hand-written survey responses. The surveys do NOT have a consistent layout.
You have an Azure subscription that contains an Azure Al Document Intelligence resource named Aldoc1.
You open Document Intelligence Studio and create a new project.
You need to extract data from the survey responses. The solution must minimize development effort.
To where should you upload the images, and which type of model should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 12
You have a collection of press releases stored as PDF files.
You need to extract text from the files and perform sentiment analysis.
Which service should you use for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
You have press releases stored as PDF files. The task involves two parts:
* Extract text
* The correct service for OCR and text extraction from images and PDFs is Azure Computer Vision (specifically, the OCR and Read API).
* While Form Recognizer can also extract text, it is primarily used for structured documents like invoices, receipts, or forms. Since the documents here are press releases (unstructured text), the best service is Computer Vision.
* Perform sentiment analysis
* Sentiment analysis falls under natural language processing (NLP).
* The correct service is Azure AI Language (Text Analytics API).
* It provides sentiment analysis, opinion mining, key phrase extraction, entity recognition, and more.
Why not other options?
* Azure Cognitive Search is used for search indexing, not OCR or sentiment.
* Form Recognizer specializes in structured document extraction, not sentiment analysis.
* Computer Vision cannot perform sentiment analysis (only visual/text extraction).
* Extract text # Computer Vision
* Perform sentiment analysis # Language
* Computer Vision Read OCR
* Language service - Sentiment Analysis
Microsoft References
NEW QUESTION # 13
You have a chatbot that uses Azure OpenAI to generate responses.
You need to upload company data by using Chat playground. The solution must ensure that the chatbot uses the data to answer user questions.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
To make a chatbot use uploaded company data from the Chat playground ("use your data") , your code must:
Create a chat request (not a plain completion), so you need the ChatCompletionsOptions type for the request options.
This is the options class used for chat completions across Azure OpenAI SDKs and is the one that supports attaching data sources (extensions).
Configure the Azure AI Search data source as a chat extension so the model grounds answers on your indexed documents.
In the SDK, this is done by adding an AzureCognitiveSearchChatExtensionConfiguration entry under the extensions/dataSources collection and setting properties like SearchKey and IndexName . This is the specific configuration object for Azure AI Search integration with Chat Completions.
Therefore, the two dropdowns should be completed as:
First dropdown: ChatCompletionsOptions()
Second dropdown: AzureCognitiveSearchChatExtensionConfiguration
This matches how "Use your data (RAG)" is implemented in Azure OpenAI-chat request + Azure AI Search chat extension-so the bot can answer questions using your uploaded/company data. Microsoft Learn Microsoft Azure AI Solution References Azure OpenAI "Use your data" (concepts): how chat uses data sources like Azure AI Search. Microsoft Learn Azure OpenAI client library for .NET (overview of chat options and extensions support). Microsoft Learn Chat Completions Options (SDK docs, shows dataSources/extensions concept in chat options).
Examples/discussion of AzureCognitiveSearchChatExtensionConfiguration usage with SearchKey
/IndexName.
NEW QUESTION # 14
You have a factory that produces food products.
You need to build a monitoring solution for staff compliance with personal protective equipment (PPE) requirements. The solution must meet the following requirements:
* identify staff who have removed masks or safety glasses.
* Perform a compliance check every 15 minutes.
* Minimize development effort.
* Minimize costs.
Which service should you use?
Answer: A
Explanation:
You need to detect PPE compliance (masks or safety glasses) on a periodic schedule (every 15 minutes) while minimizing development effort and cost.
* Why Computer Vision (Azure AI Vision)Azure AI Vision (formerly "Computer Vision") lets you analyze still images with prebuilt Image Analysis and-when needed-train a lightweight custom object detection model directly in Vision Studio without building ML pipelines. You can simply grab a frame (snapshot) from your camera feed every 15 minutes and call the Vision API-this keeps costs low because you pay per image analyzed rather than continuously processing video. Microsoft's current Vision stack supports image analysis and custom object detection via Vision Studio and v4.0 APIs, designed for scenarios like PPE detection. Microsoft Azure+1
* Why not FaceThe Face service is intended for face detection/recognition workflows. While Face can return some accessory attributes (e.g., glasses/mask confidence), Microsoft has scaled back several face attributes under Responsible AI guidance, and Face is not positioned as a general PPE-compliance detector across a scene (multiple people, full body PPE). It's therefore a poorer fit and can increase false decisions for PPE checks beyond the face region. Azure Docs+3
* Why not Azure Video Analyzer for Media (Video Indexer)Video Indexer is optimized for extracting insights from full videos (speech, people, labels, brands). Running it just to check PPE every 15 minutes is overkill and more expensive than analyzing a single still frame with Vision. In addition, Microsoft has been adjusting video services post-Azure Media Services retirement; using snapshot + Vision avoids those complexities and keeps costs minimal.
How this meets the requirements
* Identify masks/safety glasses: Use Image Analysis or a quick custom object detector in Vision Studio trained on a small set of PPE images. Microsoft Learn
* Every 15 minutes: Capture a single frame from the camera and call the Vision endpoint-simple scheduling with a timer-triggered Function or Logic App, minimal code. (General Azure pattern; Vision API is stateless per image.) Microsoft Azure
* Minimize development effort: Vision Studio provides no-code/low-code training and testing for custom detectors if the prebuilt model isn't sufficient. Microsoft Learn
* Minimize costs: Pay-per-call image analysis is cheaper than indexing entire video segments; no continuous streaming required. Microsoft Azure The answer: B. Computer Vision Microsoft References
* Azure AI Vision (product overview): image and video analysis with OCR, object detection, Image Analysis. Microsoft Azure
* What's new in Azure AI Vision: custom image classification/object detection in Vision Studio and v4.0 APIs. Microsoft Learn
* Face detection & attributes (accessories including glasses and mask)-not the right tool for scene-level PPE compliance. Microsoft Learn
* Face Detect REST API (attributes list, including glasses/mask). Microsoft Learn
* Responsible AI updates indicating changes to facial analysis attributes; facial detection/accessories remain but are limited in scope. Azure Docs
* Azure AI Video Indexer release notes/updates (video-centric use cases, ongoing adjustments post-AMS retirement).
NEW QUESTION # 15
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