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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Process and index video content - Analyze images and detect objects/features - Integrate vision capabilities into applications - Build and deploy custom vision models - Extract text and handwriting from images |
| Topic 2: Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration - Understand agent use cases and types - Build agents with Microsoft Foundry Agent Service |
| Topic 3: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
| Topic 4: Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Monitor, optimize, and secure AI solutions - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining |
| Topic 5: Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data - Implement intelligent search and retrieval |
| Topic 6: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Orchestrate multiple models and containers - Deploy and manage generative models |
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NEW QUESTION # 118
You have a Computer Vision resource named contoso1 that is hosted in the West US Azure region.
You need to use contoso1 to make a different size of a product photo by using the smart cropping feature.
How should you complete the API URL? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
westus.api.cognitive.microsoft.com
generateThumbnail
https://docs.microsoft.com/en-us/rest/api/computervision/3.1/generate-thumbnail/generate- thumbnail#examples POST https://westus.api.cognitive.microsoft.com/vision/v3.1/generateThumbnail?
width=500&height=500&smartCropping=True
Ocp-Apim-Subscription-Key: {API key}
NEW QUESTION # 119
You are building a chatbot by using the Microsoft Bot Framework Composer as shown in the exhibit. (Click the Exhibit tab.)
The chatbot contains a dialog named GetUserDetails. GetUserDetails contains a TextInput control that prompts users for their name.
The user input will be stored in a property named name.
You need to ensure that you can dispose of the property when the last active dialog ends.
Which scope should you assign to name?
Answer: A
Explanation:
Explanation
The dialog scope associates properties with the active dialog. Properties in the dialog scope are retained until the dialog ends.
Reference:
https://docs.microsoft.com/en-us/composer/concept-memory?tabs=v2x
NEW QUESTION # 120
Hotspot Question
You are building an app that will analyze text by using the Azure AI Language service.
You need to configure the app to mask the telephone number and email details in a given document.
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:
Box 1: RecognizePiiEntities
TextAnalyticsClient.RecognizePiiEntities Method
Runs a predictive model to identify a collection of entities containing Personally Identifiable Information found in the passed-in document, and categorize those entities into types such as US social security number, driver's license number, or credit card number.
Box 2: RedactedText
The characterMask policy allows the redactedText to be masked with a character, preserving the length and offset of the original text. This behavior is the existing expectation.
Reference:
https://learn.microsoft.com/en-
us/dotnet/api/azure.ai.textanalytics.textanalyticsclient.recognizepiientities
https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable- information/how-to/redact-text-pii
NEW QUESTION # 121
You are building a natural language model.
You need to enable active learning.
What should you do?
Answer: D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-queries-to-enable-active-learning
NEW QUESTION # 122
You need to create a visualization of running sales totals per quarter as shown in the following exhibit.
What should you create in Cower Bl Desktop;1
Answer: A
NEW QUESTION # 123
......
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