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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Implement Azure AI Face service - Analyze images using Azure AI Vision - Read and process documents using Azure AI Document Intelligence - Implement object detection and image classification |
| Topic 2: Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Design and implement decision automation - Integrate Azure AI services into applications |
| Topic 3: Implement Generative AI Solutions | 10-15% | - Implement prompt engineering techniques - Apply responsible AI practices - Use Azure OpenAI Service for generative AI - Integrate Azure OpenAI models into applications |
| Topic 4: Plan and Manage an Azure AI Solution | 15-20% | - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation |
| Topic 5: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Design document processing pipelines - Implement semantic and vector search - Implement Azure AI Search solutions - Create custom skills for Azure AI Search |
| Topic 6: Implement Natural Language Processing Solutions | 20-25% | - Translate text and speech - Implement speech capabilities using Azure AI Speech - Analyze text using Azure AI Language - Create conversational AI solutions with Azure AI Bot Service - Build question answering solutions |
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NEW QUESTION # 11
You are building an agent by using the Semantic Kernel. The agent will use a custom plugin. You need to ensure that the agent meets the following requirements:
* The agent must use function calling.
* All functions that match the instructions must be triggered.
* All required parameters in the function must be requested by the agent if the user fails to provide them.
How should you complete the code? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 12
You have an Azure subscription that contains an Azure OpenAl resource. Multiple different models are deployed to the resource.
You are building a chatbot by using Chat playground in Azure Al Studio.
You need to ensure that the chatbot generates text in concise formal business language. The solution must meet the following requirements:
* Reduce the cost of running the language model.
* Maintain the size of the chatbot history window.
Which two settings should you configure? To answer, select the appropriate settings in the answer are a. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 13
You are building an app that will enable users to upload images. The solution must meet the following requirements:
* Automatically suggest alt text for the images.
* Detect inappropriate images and block them.
* Minimize development effort.
You need to recommend a computer vision endpoint for each requirement.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 14
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Comprehensive Detailed ExplanationRelational databases (such as Azure SQL Database, SQL Server, or Azure Database for PostgreSQL) are designed for structured data and ACID-compliant transactions.
Let's analyze the options:
* Changes to relationships between entities
* While relational databases do handle relationships (via primary/foreign keys), this phrase alone does not describe the core usage scenario for "high volume."
* Geographically distributed writes
* This is better suited to NoSQL databases (e.g., Azure Cosmos DB) because they are optimized for global distribution and multi-region writes.
* Transactional writes
* Correct.
* Relational databases excel at handling large volumes of transactional operations (INSERT, UPDATE, DELETE) while ensuring consistency, integrity, and rollback capabilities.
* This is the primary workload for OLTP (Online Transaction Processing) systems.
* Writes that have varying data structures
* This is a use case for NoSQL/document databases like MongoDB or Azure Cosmos DB, not relational systems which require structured schema.
The answer: Transactional writes
* Azure SQL Database - transactional processing
* Data store considerations: relational vs non-relational
* OLTP vs OLAP
Microsoft References
NEW QUESTION # 15
You have an app that uses Azure Al and a custom trained classifier to identity products in images. You need to add new products to the classifier. The solution must meet the following requirements:
* Minimize how long it takes to add the products
* Minimize development effort.
Which five 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.
Answer:
Explanation:
Explanation:
To quickly add new product classes to an existing image classifier with minimal development effort, use the Custom Vision portal workflow. Vision Studio and Azure Machine Learning studio are not required for Custom Vision projects. The standard lifecycle to update a classifier is: open the project, add/upload images, label them with the correct tags, retrain to incorporate the new labels, and publish the updated iteration so the app can consume the new model via the Prediction endpoint.
Microsoft Azure AI Solution References
Azure AI Services - Custom Vision : add images, tag, train, and publish iterations from the portal.
Custom Vision documentation - Quickstart: Build a classifier in the Custom Vision website (steps: create
/open project, upload images, tag, train, publish).
NEW QUESTION # 16
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