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| Section | Weight | Objectives |
|---|---|---|
| Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models - Build conversational AI and chatbots - Implement translation and summarization |
| Implement generative AI solutions | 15-20% | - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Deploy and manage generative models |
| Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Process and index video content - Extract text and handwriting from images - Build and deploy custom vision models - Analyze images and detect objects/features |
| Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Ingest and process structured/unstructured data - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes |
| Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration |
| Plan and manage an Azure AI solution | 20-25% | - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Create and configure Azure AI resources - Monitor, optimize, and secure AI solutions - Select suitable AI models |
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질문 # 112
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 area. NOTE:
Each correct selection is worth one point.
정답：
설명：
Explanation:
You are adding a custom plugin to a Semantic Kernel-based agent and you want function calling to be enforced and self-completing:
* To register a plugin that exposes one or more callable functions to the agent, use CreatePluginFromFunctions . This builds a plugin from Kernel functions (prompt- or code-based) and makes them available for tool/function calling by the model.
* To ensure the model must call functions (and request any required parameters it doesn't have), set the prompt execution settings to FunctionChoiceBehaviour.Required . In Semantic Kernel, this corresponds to the OpenAI tool/function-calling control that forces the assistant to invoke appropriate functions. When required parameters are marked in the function's schema, the assistant will ask follow- up questions to collect them before (or while) invoking the function.
References (Microsoft Azure AI Solution)
Semantic Kernel: Plugins and Functions, ChatCompletionAgent, OpenAIPromptExecutionSettings, and FunctionChoiceBehavior for enforced tool/function calling.
질문 # 113
You are developing a monitoring system that will analyze engine sensor data, such as rotation speed, angle, temperature, and pressure. The system must generate an alert in response to atypical values.
What should you include in the solution?
정답：A
설명：
The system must analyze multiple sensor data points (rotation speed, angle, temperature, pressure) and generate alerts on anomalies.
* Application Insights # used for monitoring applications, not IoT sensor data.
* Metric alerts in Azure Monitor # works with single metrics but does not handle complex correlations.
* Univariate Anomaly Detection # only works on a single time series (e.g., just temperature).
* Multivariate Anomaly Detection # specifically built to detect anomalies across multiple correlated variables (sensor data).
Thus, the correct choice is Multivariate Anomaly Detection.
질문 # 114
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.
정답：
설명：
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
질문 # 115
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 create a web app named app1 that runs on an Azure virtual machine named vm1. Vm1 is on an Azure virtual network named vnet1.
You plan to create a new Azure Cognitive Search service named service1.
You need to ensure that app1 can connect directly to service1 without routing traffic over the public internet.
Solution: You deploy service1 and a public endpoint to a new virtual network, and you configure Azure Private Link.
Does this meet the goal?
정답：B
설명：
Scenario Recap
You have a web app app1 running on VM1 in vnet1.
You plan to create an Azure Cognitive Search service (service1).
Goal: Ensure app1 can connect to service1 without routing over the public internet.
Proposed Solution
"You deploy service1 and a public endpoint to a new virtual network, and you configure Azure Private Link." Analysis Azure Cognitive Search and Private Link:
Azure Cognitive Search supports Private Endpoints via Azure Private Link.
When you configure a private endpoint, the service is accessible privately over the virtual network and traffic does not go over the public internet.
You can still keep a public endpoint enabled optionally, but access from your VM can be restricted to the private endpoint.
Key Point: The solution specifies using a public endpoint AND a private link.
This still meets the requirement because Private Link ensures that VM1 in vnet1 communicates with service1 privately.
The existence of the public endpoint does not force traffic to go public - traffic from the private endpoint is routed over the VNet.
Conclusion
Yes, this solution meets the goal because Private Link provides secure, private connectivity to Cognitive Search, avoiding the public internet.
The Answer: A. Yes
Microsoft References
Secure access to Azure Cognitive Search with Private Link
Azure Private Link overview
질문 # 116
You have a Custom Vision resource named acvdev in a development environment.
You have a Custom Vision resource named acvprod in a production environment.
In acvdev, you build an object detection model named obj1 in a project named proj1.
You need to move obj1 to acvprod.
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.
정답：
설명：
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-tutorial-pattern#what-did-this-tutorial-accomp
질문 # 117
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아무런 노력을 하지 않고 승진이나 연봉인상을 꿈꾸고 있는 분이라면 이 글을 검색해낼수 없었을것입니다. 승진이나 연봉인상을 꿈꾸면 승진과 연봉인상을 시켜주는 회사에 능력을 과시해야 합니다. IT인증시험은 국제적으로 승인해주는 자격증을 취득하는 시험입니다. KoreaDumps의Microsoft인증 AI-102덤프의 도움으로 Microsoft인증 AI-102시험을 패스하여 자격증을 취득하면 승진이나 연봉인상의 꿈이 이루어집니다. 결코 꿈은 이루어질것입니다.
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