AI-102 Implement generative AI solutions Practice Test 7 — 15 Questions

Question 1

Your organization uses Microsoft 365 Copilot. You want to ensure that Copilot only uses data from your Microsoft 365 tenant and does not access external sources. Which setting should you configure?

Accepted Answer

Configure Copilot to use only Microsoft Graph data.. Option B is correct because configuring Copilot to use only Microsoft Graph data ensures that the AI model retrieves content exclusively from your Microsoft 365 tenant (e.g., emails, documents, calendar events) via Microsoft Graph APIs. This setting explicitly restricts Copilot from querying external sources like the public web or third-party services, aligning with the requirement to keep data within the tenant boundary.

Answer

Disable 'Allow Copilot to use external data' in the Copilot settings.

Answer

Enable content filtering for Copilot.

Question 2

Which TWO actions can you take to reduce the cost of using Azure OpenAI Service for a chat application?

Accepted Answer

Set the max_tokens parameter to a lower value.. Option C is correct because reducing the max_tokens parameter directly limits the number of tokens generated per API call, which lowers the cost since Azure OpenAI Service bills per token (both input and output). By capping the response length, you avoid paying for unnecessarily long completions.

Answer

Increase the frequency penalty.

Answer

Enable content filtering.

Answer

Increase the max_tokens parameter to allow longer responses.

Question 3

Which THREE components are required to build a custom chat application using Azure OpenAI Service that can answer questions based on your own private data?

Accepted Answer

The 'Add your data' feature configured in Azure OpenAI Studio.. Option A is correct because the 'Add your data' feature in Azure OpenAI Studio provides a no-code interface to connect your private data sources (e.g., Azure Blob Storage, local files) to an Azure OpenAI chat model. It automatically chunks the data, creates an Azure AI Search index, and configures the retrieval-augmented generation (RAG) pipeline, enabling the model to answer questions grounded in your proprietary content without fine-tuning.

Answer

A fine-tuned custom model.

Answer

An Azure OpenAI embeddings model deployment.

Question 4

Which TWO features of Azure AI Content Safety can help you moderate user-generated content in a social media application?

Accepted Answer

Self-harm content detection.. Self-harm content detection (A) is a feature of Azure AI Content Safety that specifically identifies text or images related to self-harm, which is a critical category for moderating user-generated content in social media to prevent harm and comply with safety policies. Hate speech severity detection (B) is another core feature that classifies hate speech into severity levels (e.g., low, medium, high), enabling nuanced moderation of offensive content.

Answer

PII redaction.

Answer

Groundedness detection.

Answer

Prompt injection detection.

Question 5

Which THREE are valid parameters when calling the Azure OpenAI Service chat completions API?

Accepted Answer

messages. The `messages` parameter is required in the Azure OpenAI Service chat completions API call. It defines the conversation history and user input as an array of message objects, each with a `role` (system, user, assistant) and `content`. Without this parameter, the API cannot determine the context or prompt for generating a response.

Answer

index_name

Answer

embedding_model

Question 6

Refer to the exhibit. You are troubleshooting an Azure OpenAI API call that is returning incomplete responses. The response stops mid-sentence. Which parameter should you adjust?

Accepted Answer

Increase max_tokens to 1000.. The `max_tokens` parameter controls the maximum number of tokens the model can generate in a single response. When a response stops mid-sentence, it typically means the token limit was reached before the model could complete its output. Increasing `max_tokens` to 1000 provides more room for the model to finish its generation, resolving the truncation issue.

Answer

Remove the stop parameter.

Answer

Increase temperature to 1.0.

Answer

Increase top_p to 1.0.

Question 7

Refer to the exhibit. You are using Microsoft Graph to retrieve user information for use in a Microsoft 365 Copilot extension. The response shows that the mail and mobilePhone fields are null. What is the most likely reason?

Accepted Answer

The user has not configured those properties in their Microsoft Entra ID profile.. The mail and mobilePhone fields are null because the user has not populated these attributes in their Microsoft Entra ID (formerly Azure AD) profile. Microsoft Graph returns the actual stored values for these properties; if they are empty or unset, the API response will show null. This is the most common and straightforward reason for null values in user profile fields.

Answer

The API call required additional permissions.

Answer

The user is a guest user.

Answer

The user does not exist in the tenant.

Question 8

Refer to the exhibit. You are deploying an Azure AI Services resource using an ARM template. After deployment, you cannot access the resource from any client, including the Azure portal. What is the most likely cause?

Accepted Answer

The networkAcls defaultAction is set to Deny with no allowed IP or virtual network rules.. The networkAcls defaultAction set to Deny with no allowed IP or virtual network rules blocks all traffic to the Azure AI Services resource, including requests from the Azure portal and any client. This is because the default network access control list (ACL) denies all traffic unless explicitly permitted by IP rules or virtual network rules, rendering the resource inaccessible even for management operations.

Answer

The SKU S0 does not support network restrictions.

Answer

The cognitiveServiceName conflicts with an existing resource.

Answer

The virtualNetworkRules array is empty.

Question 9

Refer to the exhibit. You are configuring a system message for an Azure OpenAI deployment. The assistant is still generating harmful code despite the instruction. Which additional measure should you implement?

Accepted Answer

Enable Azure AI Content Safety with a custom blocklist for harmful code.. Option D is correct because Azure AI Content Safety provides a dedicated content filtering layer that can block harmful code generation at the inference level, regardless of the system message. A custom blocklist allows you to define specific patterns (e.g., code snippets for malware) that the model is prohibited from outputting, enforcing safety beyond prompt instructions.

Answer

Fine-tune the model on safe code examples.

Answer

Lower the temperature parameter to 0.

Answer

Add more examples to the prompt.

Question 10

Your organization is building a chatbot using Azure OpenAI Service. The chatbot must provide citations from a set of internal documents stored in Azure Blob Storage. You need to configure the solution to minimize token usage while ensuring citations are accurate. Which approach should you use?

Accepted Answer

Use Azure OpenAI on your data with Azure Cognitive Search for hybrid retrieval. Option B is correct because Azure OpenAI on your data with Azure Cognitive Search uses a hybrid retrieval approach (vector + keyword), which is more token-efficient than embedding all content into the prompt. Option A is wrong because embedding entire documents wastes tokens. Option C is wrong because it lacks retrieval. Option D is wrong because fine-tuning does not support dynamic document citation.

Answer

Embed all document content into the system prompt

Answer

Fine-tune a model on the documents so it can recall them from memory

Answer

Use a large context window model (e.g., 32K) and include all documents in the prompt

Question 11

You are deploying a conversational AI solution using Microsoft Copilot Studio. The solution must comply with organizational data loss prevention (DLP) policies by preventing sensitive data from being sent to the underlying Azure OpenAI model. What should you configure?

Accepted Answer

Define DLP policies in Microsoft 365 compliance center and apply to Copilot Studio. Option B is correct because Microsoft Copilot Studio integrates with Microsoft 365 DLP policies to prevent sensitive data from being sent to the underlying Azure OpenAI model. By defining DLP policies in the Microsoft 365 compliance center and applying them to Copilot Studio, you can enforce data loss prevention rules that block or restrict the transmission of sensitive information (e.g., credit card numbers, social security numbers) to the generative AI backend. This ensures compliance with organizational security requirements without modifying the AI model itself.

Answer

Configure content filters in Azure OpenAI Studio

Answer

Enable Azure AI Content Safety in the bot's generative AI configuration

Answer

Set the temperature parameter to 0 to reduce variability

Question 12

A company wants to generate product descriptions for thousands of items using an Azure OpenAI GPT-4 model. They need to ensure the descriptions match a consistent brand voice. Which approach is most efficient and cost-effective?

Accepted Answer

Set a system message with brand voice guidelines and use few-shot examples. Option C is correct because setting a system message with brand voice guidelines and providing few-shot examples allows the GPT-4 model to consistently apply the desired tone and style across all product descriptions without retraining. This approach is efficient and cost-effective as it avoids the high compute and data preparation costs of fine-tuning, while still enabling precise control over output through in-context learning.

Answer

Write a separate prompt for each product category

Answer

Use Azure OpenAI on your data with a vector database of brand guidelines

Answer

Fine-tune a base model on existing product descriptions

Question 13

You are developing a solution that uses Azure Document Intelligence to extract data from invoices and then uses Azure OpenAI to summarize the extracted data. The solution occasionally produces summaries that omit key fields like the invoice total. What should you do to improve accuracy?

Accepted Answer

Define a structured prompt that explicitly requests each field and provide examples. Option D is correct because the issue is that the summarization prompt lacks explicit instructions for which fields to include. By defining a structured prompt that explicitly requests each key field (e.g., invoice total, date, vendor) and providing examples, you guide the Azure OpenAI model to consistently extract and include those fields in the summary, reducing omission errors. This approach leverages prompt engineering to improve output reliability without changing model parameters or size.

Answer

Set temperature to 0 to make the output more deterministic

Answer

Use a larger model like GPT-4 instead of GPT-3.5

Answer

Increase the max_tokens parameter

Question 14

Your Azure OpenAI application experiences high latency during peak hours. You have already scaled up the deployment to the maximum PTUs. What is the most effective next step to reduce latency?

Accepted Answer

Create multiple deployments across different regions and use Azure Traffic Manager to distribute requests. When PTU deployment is already maxed out, the bottleneck is the capacity of a single regional deployment. Distributing requests across multiple regional deployments via Azure Traffic Manager (using performance or geographic routing) spreads the load, reducing per-deployment contention and lowering latency. This approach leverages regional redundancy and global load balancing without requiring a model change or sacrificing quality.

Answer

Use Azure OpenAI's global deployment with the same PTU

Answer

Switch from GPT-4 to GPT-3.5-turbo

Answer

Increase the token limit per request

Question 15

You are building a generative AI solution using Azure Machine Learning prompt flow. The solution must allow business analysts without coding experience to modify prompts and evaluate different model versions. What should you do?

Accepted Answer

Use Azure Machine Learning prompt flow with the visual designer and variant management. Option C is correct because prompt flow in Azure ML provides a visual designer and evaluation tools suitable for non-coders. Option A is wrong because direct API calls require coding. Option B is wrong because it's a different service. Option D is wrong because it's not a visual tool.

Answer

Provide the analysts with a Jupyter notebook using the OpenAI Python SDK

Answer

Deploy a chatbot in Microsoft Copilot Studio and let analysts configure it

Answer

Implement a custom web UI using Azure Static Web Apps and Azure Functions