AI-102 Practice Test 3 — 10 Questions

Question 1

Your company uses Azure OpenAI to generate code snippets. Developers need to ensure that the generated code does not contain security vulnerabilities. What should you implement?

Accepted Answer

Integrate a static code analysis tool into the CI/CD pipeline to scan generated code. Integrating a static code analysis tool (e.g., Microsoft Defender for DevOps, SonarQube, or Checkmarx) into the CI/CD pipeline allows automated scanning of generated code for security vulnerabilities before deployment. This approach directly addresses the requirement to ensure generated code is free of vulnerabilities, as Azure OpenAI content filters are not designed to detect code-level security flaws like SQL injection or buffer overflows.

Answer

Set usage quotas to limit the number of code generation requests

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Fine-tune the model on a dataset of secure code examples

Answer

Configure Azure OpenAI content filters to block vulnerable code

Question 2

A company wants to use Azure AI Translator to translate customer emails from English to French. They need to ensure that the translation preserves the tone and formality of the original text. What should they configure in the request?

Accepted Answer

Set the 'formality' parameter to the desired level (e.g., 'formal' or 'informal').. Azure AI Translator provides a 'formality' parameter that allows you to specify the desired level of formality (e.g., 'formal' or 'informal') in the translated text. This parameter directly controls the tone and register of the output, ensuring that the translation preserves the original email's tone and formality, which is critical for customer communications.

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Set the 'category' parameter to 'general' to use a standard translation model.

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Set the 'scope' parameter to 'document' to ensure context-aware translation.

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Set the 'language' parameter to 'fr' and the 'from' parameter to 'en'.

Question 3

You are using Microsoft Copilot Studio to create an agent that handles customer support. The agent needs to understand the user's intent from free-text input. Which feature should you use to map user utterances to specific topics?

Accepted Answer

Define trigger phrases for each topic. In Microsoft Copilot Studio, trigger phrases are the primary mechanism for mapping user utterances to specific topics. When a user types a free-text input, the agent's natural language understanding (NLU) engine compares the input against the defined trigger phrases for each topic. The topic with the highest confidence score based on semantic similarity is triggered, enabling intent recognition without requiring exact keyword matches.

Answer

Configure variables to capture user input

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Add actions to process the input

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Create custom entities to extract key phrases

Question 4

You need to monitor usage and costs of your Azure OpenAI Service deployments. Which Azure tool should you use?

Accepted Answer

Azure Cost Management + Billing. Azure Cost Management + Billing is the correct tool for monitoring usage and costs of Azure OpenAI Service deployments because it provides detailed cost analysis, budget tracking, and usage reports across all Azure services. It allows you to set budgets, create cost alerts, and analyze spending patterns specifically for OpenAI model deployments, including per-model and per-region cost breakdowns.

Answer

Azure Monitor

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Azure Service Health

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Azure Advisor

Question 5

A developer is building an agent using the Microsoft Bot Framework SDK in C#. The agent must authenticate users via Microsoft Entra ID and maintain state across conversations. The solution must store user preferences (e.g., language, timezone) in Azure Cosmos DB. Which state management approach should the developer use?

Accepted Answer

Use UserState with Cosmos DB Storage.. The developer needs to persist user preferences across conversations, which requires UserState (not ConversationState, which is scoped to a single conversation). Cosmos DB Storage is the appropriate choice for durable, scalable, and low-latency storage of user-specific data, and it integrates directly with the Bot Framework SDK's `CosmosDbPartitionedStorage` class.

Answer

Use the Bot State Service (deprecated).

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Use UserState with Blob Storage.

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Use ConversationState with Memory Storage.

Question 6

You are designing a solution that uses Azure AI Language to analyze customer feedback. The solution must detect sentiment, extract key phrases, and identify named entities. Which feature should you use?

Accepted Answer

Azure AI Language service. The Azure AI Language service provides pre-built capabilities for sentiment analysis, key phrase extraction, and named entity recognition (NER) as part of its text analytics features. These three tasks are directly supported by the service's Analyze API, making it the correct choice for analyzing customer feedback text.

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Azure AI Speech service

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Azure AI Computer Vision

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Translator API

Question 7

Refer to the exhibit. A developer is configuring a QnA Maker skill for a bot. The skill fails to respond to queries. What is the most likely issue?

Accepted Answer

The modelUrl points to the authoring API instead of the runtime endpoint.. The modelUrl uses the v4.0 API, but the endpoint key and kbId are hardcoded and may be invalid or expired. Additionally, the URL should be for the runtime endpoint, not the authoring API.

Answer

The kbId is not published.

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The skill is not deployed.

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The endpointKey is incorrect.

Question 8

You have deployed a generative AI model using Azure Machine Learning. The model is used for generating financial reports. You need to monitor the model's performance and detect data drift in the input data. What should you use?

Accepted Answer

Azure Machine Learning data drift monitoring. Azure Machine Learning data drift monitoring is the correct choice because it is specifically designed to detect statistical changes in input data over time, which is critical for generative AI models used in financial reporting where data distributions can shift due to market changes or new regulations. It compares the current input data distribution against a baseline dataset using metrics like Wasserstein distance or Population Stability Index, and triggers alerts when drift exceeds a threshold. This ensures the model's outputs remain reliable and compliant, which is a core requirement for generative AI solutions in regulated industries.

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Azure Monitor

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Application Insights

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Azure AI Language

Question 9

A company is building a solution to analyze customer reviews images using Azure AI Vision. They need to extract text from images that may contain both printed and handwritten text. Which feature should they use?

Accepted Answer

Read API. The Read API is the correct choice because it is specifically designed to extract text from images containing both printed and handwritten text, using advanced OCR capabilities that support mixed content. Unlike the OCR API, which is optimized for printed text only, the Read API leverages deep learning models to handle varied handwriting styles and complex layouts, making it ideal for analyzing customer review images.

Answer

Custom Vision

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OCR API (optical character recognition)

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Azure AI Document Intelligence

Question 10

Refer to the exhibit. You are designing a Data Factory pipeline to perform sentiment analysis on a text column. The pipeline fails with a 'BadRequest' error. What is the most likely issue?

Accepted Answer

The input format is incorrect; it should be a JSON array of documents. The Cognitive Services activity in Azure Data Factory that performs sentiment analysis expects input in the form of a JSON array of documents, each containing an 'id' and 'text' field. A 'BadRequest' error typically indicates that the input format is incorrect, such as passing a single string or an improperly structured object instead of the required array. The other options are less likely because the error is specifically related to the request payload format.

Answer

The output variable 'sentimentResult' is not defined

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The activity type should be 'AzureFunction'

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The linked service name is misspelled