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| Section | Objectives |
|---|---|
| Topic 1: Implement Generative AI Solutions | - Build retrieval-augmented generation (RAG) solutions - Implement Azure OpenAI Service solutions - Integrate prompt engineering techniques |
| Topic 2: Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Manage security, compliance, and responsible AI - Plan solution requirements and architecture |
| Topic 3: Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Build Azure AI Search solutions - Implement document intelligence solutions |
| Topic 4: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language - Implement question answering and conversational AI |
| Topic 5: Implement Computer Vision Solutions | - Extract information using OCR and form recognition - Implement custom vision models - Analyze images and videos using Azure AI Vision |
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NEW QUESTION # 35
You are building an internet-based training solution. The solution requires that a user's camera and microphone remain enabled.
You need to monitor a video stream of the user and detect when the user asks an instructor a question. The solution must minimize development effort.
What should you include in the solution?
Answer: A
NEW QUESTION # 36
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:
Upload to: An Azure Storage account
* Model type: Custom neural
You have 1,000 scanned hand-written survey responses with no consistent layout. The goal is to extract data while minimizing development effort.
Step 1: Upload location
* For Azure AI Document Intelligence (formerly Form Recognizer), training data (images, PDFs) must be placed in a container in an Azure Storage account.
* Options like Cosmos DB or Azure Files share are not valid training data sources for Document Intelligence.
* Therefore, you upload the survey images to Azure Storage account.
Step 2: Model type
* The surveys are handwritten and do not have a consistent layout.
* Custom template models work only when the layout is fixed and consistent (e.g., invoices with the same fields in the same place).
* Identity document (ID) model is a prebuilt model for passports, driver's licenses, etc., not for surveys.
* Custom neural model is designed to handle unstructured or variable-layout forms, including handwritten content. This best fits the survey scenario.
Thus, the correct configuration is:
* Upload to Azure Storage account
* Use Custom neural model
* Upload to: An Azure Storage account
* Model type: Custom neural
* Azure AI Document Intelligence - Custom models
* Custom neural vs custom template models
* Train a custom model with Azure Storage input
Microsoft References
NEW QUESTION # 37
You need to develop an extract solution for the receipt images. The solution must meet the document processing requirements and the technical requirements.
You upload the receipt images to the From Recognizer API for analysis, and the API returns the following JSON.
Which expression should you use to trigger a manual review of the extracted information by a member of the Consultant-Bookkeeper group?
Answer: A
Explanation:
Explanation
Need to specify the field name, and then use < 0.7 to handle trigger if confidence score is less than 70%.
Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/api-v2-0/reference-sdk-api-v2-0
NEW QUESTION # 38
You have an Azure subscription that contains an Azure OpenAI resource named OpenAI1 and a user named User1.
You need to ensure that User1 can upload datasets to OpenA11 and finetune the existing models. The solution must follow the principle of least privilege.
Which role should you assign to User!?
Answer: C
Explanation:
* A user User1 must be able to upload datasets and fine-tune existing models in Azure OpenAI.
* The role must follow principle of least privilege.
Role analysis:
* A. Cognitive Services Contributor: Too broad; allows management of all Cognitive Services resources, not least privilege.
* B. Contributor: Overly permissive; allows full management rights on the entire resource, not just OpenAI.
* C. Cognitive Services OpenAI User: Grants permissions only to use models (query endpoints). Does not allow fine-tuning or dataset upload.
* D. Cognitive Services OpenAI Contributor: Correct role. This provides the ability to manage OpenAI resources, including uploading training data and fine-tuning models.
The answer: D. Cognitive Services OpenAI Contributor
Microsoft Reference:
* Azure RBAC roles for Azure OpenAI
* Built-in roles: Cognitive Services OpenAI Contributor
NEW QUESTION # 39
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 40
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