AI-102 Implement generative AI solutions Practice Test 10 — 15 Questions

Question 1

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?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Enable Azure AI Content Safety with a custom blocklist for harmful code.. 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.

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Fine-tune the model on safe code examples.

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Lower the temperature parameter to 0.

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Add more examples to the prompt.

Question 2

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. Azure OpenAI on your data with Azure Cognitive Search for hybrid retrieval combines vector search and keyword search to efficiently find relevant document chunks from Azure Blob Storage, minimizing token usage by only sending the most pertinent content to the model for citation generation. This approach ensures accurate citations without embedding all documents into the prompt or relying on model memory.

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Embed all document content into the system prompt

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

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

Question 3

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. 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.

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Configure content filters in Azure OpenAI Studio

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

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Set the temperature parameter to 0 to reduce variability

Question 4

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. 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

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

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Fine-tune a base model on existing product descriptions

Question 5

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. 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.

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Set temperature to 0 to make the output more deterministic

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

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Increase the max_tokens parameter

Question 6

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. Azure Machine Learning prompt flow provides a visual designer that enables non-technical users to modify prompts without coding, and its variant management feature allows them to evaluate different model versions side-by-side. This directly addresses the requirement for business analysts to iteratively refine prompts and compare model outputs in a controlled, no-code environment.

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

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

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

Question 7

You deploy a chat application using Azure OpenAI Service. Users report that the model sometimes generates inappropriate content. You need to implement a safety system that can be customized for your organization's policies. What should you use?

Accepted Answer

Use Azure AI Content Safety with custom categories and severity thresholds. Azure AI Content Safety provides a customizable content moderation service that allows you to define custom categories and severity thresholds aligned with your organization's specific policies. This enables you to filter inappropriate content beyond the default filters, giving you granular control over what the model generates.

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Use the content filter system in Azure OpenAI Studio

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Apply responsible AI templates from Azure AI Studio

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Configure Microsoft Entra ID Conditional Access policies

Question 8

Your organization uses Azure OpenAI Service with a data source configured as 'Azure OpenAI on your data'. You notice that the responses include outdated information even though the underlying data source has been updated. What is the most likely cause?

Accepted Answer

The index in Azure Cognitive Search has not been refreshed. When using Azure OpenAI Service with 'Azure OpenAI on your data', the responses are generated by querying an Azure Cognitive Search index that contains your data. If the underlying data source has been updated but the responses still include outdated information, the most likely cause is that the index in Azure Cognitive Search has not been refreshed to reflect those updates. The model itself does not store or cache the data; it relies on the index at query time, so an outdated index directly leads to outdated responses.

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The model is using a cached version of the prompt

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The data source is configured to sync only daily

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The Azure CDN is caching the responses

Question 9

You need to provide a generative AI solution that can answer questions based on a large set of PDF documents stored in Azure Blob Storage. The solution must support natural language queries and return citations from the documents. Which Azure service combination should you use?

Accepted Answer

Azure Cognitive Search and Azure OpenAI Service with 'on your data'. Azure Cognitive Search provides the indexing and retrieval capabilities for the PDF content, while Azure OpenAI Service with the 'on your data' feature enables natural language querying and generates answers grounded in the indexed documents, including citations. This combination directly supports the requirement to query a large set of PDFs in Azure Blob Storage and return citations.

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Azure Machine Learning and Azure Kubernetes Service

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Azure AI Bot Service and Azure Functions

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Azure AI Document Intelligence and Azure AI Translator

Question 10

Which TWO are valid ways to manage cost when using Azure OpenAI Service in a production application?

Accepted Answer

Use a smaller model like GPT-3.5-turbo instead of GPT-4 for simpler tasks. Using a smaller model like GPT-3.5-turbo for simpler tasks directly reduces the per-token cost compared to GPT-4, which is significantly more expensive. Azure OpenAI Service charges based on model tier and token usage, so selecting the appropriate model for the task complexity is a primary cost management strategy.

Answer

Fine-tune the model to reduce the number of examples needed in prompts

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Increase the temperature parameter to 1.0

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Provision more PTUs to get a lower rate per token

Question 11

Which THREE components are required to build a custom copilot using Microsoft Copilot Studio that can answer questions from a SharePoint document library?

Accepted Answer

A Microsoft Copilot Studio copilot. A Microsoft Copilot Studio copilot is the core conversational interface that orchestrates the interaction. Without the copilot itself, there is no runtime environment to process user queries, manage conversation state, or invoke configured knowledge sources. It is the mandatory host for all custom copilot functionality.

Answer

A Power Automate flow to trigger the copilot

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An Azure OpenAI Service deployment

Question 12

Which TWO statements about Azure OpenAI Service content filters are true?

Accepted Answer

They can be configured with severity levels (low, medium, high). Azure OpenAI Service content filters can be configured with severity levels (low, medium, high) to control the strictness of filtering for each content category. This allows administrators to fine-tune the filter sensitivity based on their application's risk tolerance and compliance requirements.

Answer

They only filter the output of the model

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They cannot be customized for specific use cases

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They are bypassed when using PTU deployments

Question 13

You are developing a generative AI application that uses Azure OpenAI Service to summarize large documents. The application experiences high latency when processing requests. You need to reduce the latency without changing the model. What should you do?

Accepted Answer

Reduce the max_tokens parameter in the API request. Reducing the max_tokens parameter limits the length of the generated response, which directly reduces the processing time required by the Azure OpenAI Service to produce the output. Since latency is caused by the model generating a long sequence of tokens, capping the output tokens decreases the number of autoregressive decoding steps, thereby lowering response time without altering the underlying model.

Answer

Increase the temperature parameter

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Increase the top_p parameter

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Increase the max_tokens parameter

Question 14

You are using Azure OpenAI Service to generate code snippets for a development team. You notice that the generated code sometimes contains security vulnerabilities. You need to minimize the risk of generating insecure code while maintaining productivity. What should you do?

Accepted Answer

Use system messages to instruct the model to prioritize security. System messages in Azure OpenAI Service allow you to set the context and behavior of the model, including instructing it to prioritize security when generating code. This approach directly influences the model's output without requiring retraining or sacrificing flexibility, making it the most effective way to reduce security vulnerabilities while maintaining productivity.

Answer

Fine-tune the model on a dataset of secure code

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Set the temperature parameter to 0

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Disable content filtering to allow more flexibility

Question 15

You are using Azure OpenAI Service to generate marketing copy. The marketing team reports that the generated content sometimes contains factual inaccuracies. You need to improve the factual accuracy of the generated content. What should you do?

Accepted Answer

Include relevant context and facts in the prompt. The most effective way to improve factual accuracy in Azure OpenAI generations is to ground the model with relevant context and facts in the prompt — this is the core of Retrieval-Augmented Generation (RAG). By supplying authoritative source content, the model conditions its output on verified information rather than relying solely on parametric memory, which reduces hallucinations. This directly addresses the marketing team's complaint about factual inaccuracies.

Answer

Increase the max_tokens parameter

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Decrease the temperature parameter

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Disable content filtering