AI-102 Multiple Select — 20 Questions

Question 1

A developer is using Azure OpenAI to generate code snippets. The developer needs to ensure that the generated code does not contain security vulnerabilities. Which TWO actions should the developer take? (Choose two.)

Accepted Answer

Include examples of secure coding practices in the prompt.. Option A is correct because including examples of secure coding practices in the prompt (few-shot prompting) directly guides the model to generate code that follows those patterns. This technique leverages in-context learning, where the model uses the provided examples to shape its output, reducing the likelihood of producing insecure code without requiring fine-tuning or external filtering.

Answer

Set the max_tokens parameter to a high value to allow longer outputs.

Answer

Fine-tune the model on a dataset containing examples of insecure code.

Answer

Add a system message that instructs the model to never generate insecure code.

Question 2

Which TWO Azure services can be used to detect and redact PII from images containing text? (Choose two.)

Accepted Answer

Azure AI Content Safety.. Azure AI Content Safety can detect and redact PII from images containing text by analyzing the extracted text for sensitive information such as personal identifiers and applying redaction. Azure Computer Vision (OCR) provides the underlying text extraction capability, and when combined with Content Safety's PII detection, enables end-to-end redaction of PII from images.

Answer

Azure Form Recognizer.

Answer

Azure Video Analyzer for Media.

Answer

Azure Cognitive Search.

Question 3

A company wants to deploy an agent using Azure Bot Service that integrates with Microsoft Teams. Which THREE steps should the team take?

Accepted Answer

Use the Bot Framework SDK to build the bot with Teams-specific features.. Option A is correct because the Bot Framework SDK provides the necessary APIs and tools to build bots that can leverage Teams-specific features such as adaptive cards, messaging extensions, and task modules. Without the SDK, you cannot implement the channel-specific logic required for Teams integration.

Answer

Deploy the bot code to an Azure Function.

Answer

Write the bot in C# using Azure SDK for .NET.

Question 4

An agent uses Azure OpenAI with function calling to perform actions. The agent is not executing functions correctly. Which THREE factors should the team check to diagnose the issue?

Accepted Answer

The token limit is too low, truncating the function definitions.. Option B is correct because if the token limit is too low, the model may not receive the full function definitions, causing it to omit or misinterpret available functions. This truncation prevents the model from correctly selecting or formatting function calls, leading to execution failures.

Answer

The temperature parameter is set too high.

Answer

The model version is outdated.

Question 5

Which TWO actions can reduce the cost of using Azure Custom Vision for image classification? (Choose two.)

Accepted Answer

Use the compact domain for faster training.. Option B is correct because using the compact domain in Azure Custom Vision reduces model complexity and training time, which directly lowers compute costs. Compact domains are optimized for edge deployment and require fewer resources, making them more cost-effective for image classification tasks.

Answer

Include negative samples in the dataset.

Answer

Use a larger image size for higher accuracy.

Answer

Increase the number of training iterations.

Question 6

Which THREE are required to build a custom video indexing solution using Azure Video Analyzer for Media? (Choose three.)

Accepted Answer

An Azure Video Analyzer for Media account.. An Azure Video Analyzer for Media account is required because it is the core service that provides the video indexing capabilities, including AI-powered insights like speech transcription, face detection, and sentiment analysis. Without this account, you cannot access the indexing APIs or manage indexed videos.

Answer

A custom indexing pipeline.

Answer

A custom language model.

Question 7

A company is building an agent that uses Azure OpenAI to answer questions from a large document library. The agent must use a Retrieval Augmented Generation (RAG) pattern. Which TWO actions should the team take to implement RAG effectively?

Accepted Answer

Index the documents into a vector database like Azure Cognitive Search.. Option C is correct because indexing documents into a vector database like Azure Cognitive Search enables efficient similarity search over embeddings, which is the retrieval foundation of RAG. This allows the system to quickly find the most relevant document chunks based on semantic meaning, rather than relying on the model to memorize or be fine-tuned on the entire library.

Answer

Ensure the model is large enough to memorize the entire document library.

Answer

Fine-tune the Azure OpenAI model on the document library.

Answer

Train a custom language model from scratch.

Question 8

An agent uses Azure AI Language to perform sentiment analysis on customer feedback. The team notices that the sentiment scores are sometimes inaccurate for negative feedback. Which TWO improvements should the team consider?

Accepted Answer

Pre-process the text to handle negations and sarcasm.. Option A is correct because Azure AI Language's pre-built sentiment analysis models can struggle with linguistic nuances like negations (e.g., 'not good') and sarcasm (e.g., 'Great, another delay'). Pre-processing the text to explicitly handle these patterns—such as by expanding contractions or using negation detection—can improve the accuracy of the sentiment scores before they are passed to the model.

Answer

Switch to a different language model without fine-tuning.

Answer

Increase the number of decimal places in the sentiment score.

Answer

Increase the confidence threshold for positive sentiment.

Question 9

A company is designing a solution that uses Azure Cognitive Services for text analytics. The solution must meet the following requirements: 
- Detect sentiment in customer feedback. 
- Extract key phrases from the feedback. 
- Identify the language of the feedback automatically. 
- Ensure that the solution can scale to handle thousands of requests per second. 
Which TWO actions should the company take?

Accepted Answer

Use the Text Analytics API for sentiment analysis and key phrase extraction.. Option B is correct because the Text Analytics API (part of Azure Cognitive Services for Language) provides built-in capabilities for sentiment analysis, key phrase extraction, and language detection within a single API call. This eliminates the need for separate services and directly satisfies the requirements for detecting sentiment, extracting key phrases, and identifying language automatically.

Answer

Deploy a separate Language Detection service for language identification.

Answer

Use the Free pricing tier to reduce costs.

Answer

Use Azure Functions to aggregate results from multiple API calls.

Question 10

A company uses Azure Content Moderator to moderate user-generated content. They need to ensure that content moderation workflows comply with regional regulations. Which TWO actions should they take?

Accepted Answer

Deploy Content Moderator resources in the required geographic regions to meet data residency requirements.. Deploying Azure Content Moderator resources in the required geographic regions ensures that user-generated content is processed and stored within specific data boundaries, directly addressing data residency regulations. This is a fundamental compliance requirement because Azure resources are region-bound, and data does not leave the selected region unless explicitly configured otherwise.

Answer

Use the free tier to reduce costs while meeting compliance needs.

Answer

Enable geo-tagging on the Content Moderator API to automatically apply region-specific moderation.

Answer

Configure the API to automatically reject any content that violates regional laws.

Question 11

A company uses Azure Document Intelligence to extract data from tax forms. They need to improve accuracy for a specific field. Which TWO actions should they take?

Accepted Answer

Label more examples of the specific field in the training set. Option A is correct because labeling more examples of the specific field in the training set directly provides the custom model with additional ground-truth annotations for that field. This increases the model's ability to learn the variations in handwriting, formatting, and layout for that field, which is the most effective way to improve extraction accuracy for a targeted field in Azure Document Intelligence custom models.

Answer

Increase the batch size in the analysis request

Answer

Reduce the image resolution to 200 DPI

Answer

Use the prebuilt-tax.us model

Question 12

Which THREE components are required to build a custom named entity recognition (NER) model in Azure Cognitive Service for Language?

Accepted Answer

A set of labeled documents for training.. Option C is correct because a custom NER model in Azure Cognitive Service for Language requires a set of labeled documents for training. These labeled documents define the entities and their spans within text, which the model uses to learn patterns for extraction. Without labeled data, the model cannot be trained to recognize custom entities.

Answer

A QnA Maker knowledge base for entity definitions.

Answer

A LUIS application to handle entity extraction.

Question 13

A company uses Azure Cognitive Search to index customer support emails. They need to implement a custom skill that extracts the sentiment of the email body and also identifies the primary product mentioned. The custom skill is a Python function deployed as an Azure Function. They want to ensure the skill can process multiple documents concurrently and handle errors gracefully. Which THREE configurations should they apply?

Accepted Answer

Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill.. Option B is correct because the custom skill must receive the email body text for sentiment analysis and the product field from a prior skill (e.g., a key phrase extraction or entity recognition skill) to identify the primary product. This ensures the Azure Function has all required inputs to produce the desired outputs (sentiment score and product name).

Answer

Set continueOnError to false to ensure that if the skill fails for one document, the entire indexer run stops.

Answer

Set the context property to '/document/pages/*' to process each page of the email individually.

Question 14

Which THREE actions should an engineer take when deploying a custom question answering project in Azure Cognitive Service for Language?

Accepted Answer

Set up a multi-turn extraction policy for follow-up questions.. Option B is correct because multi-turn extraction is a core feature of custom question answering that allows the system to handle follow-up questions by maintaining context across turns. This is essential for conversational flows where a user's subsequent query depends on the previous answer, and it is configured via the project settings in Language Studio.

Answer

Integrate LUIS for intent detection.

Answer

Configure a single-turn extraction policy.

Question 15

Which TWO actions should you take to optimize a custom text classification model in Azure Cognitive Service for Language?

Accepted Answer

Ensure that training examples for different labels do not have overlapping content.. Option A is correct because overlapping content between labels (e.g., the same text appearing in both 'positive' and 'negative' training examples) confuses the custom text classification model, leading to poor decision boundaries. Azure Cognitive Service for Language uses a multi-class or multi-label classifier that learns distinct patterns for each label; overlapping content introduces ambiguity, reducing precision and recall. Ensuring distinct, non-overlapping training examples per label helps the model learn clear, separable features.

Answer

Oversample the minority classes to balance the dataset.

Answer

Remove all stop words from the training data.

Answer

Remove examples with neutral sentiment to focus on positive and negative classes.

Question 16

Which TWO actions are required to enable a custom chatbot built with Azure OpenAI to answer questions based on a company's internal PDF documents?

Accepted Answer

Ingest the PDFs into an Azure Cognitive Search index. Option D is correct because Azure Cognitive Search provides the indexing and retrieval capabilities needed to make PDF content searchable. By ingesting PDFs into an Azure Cognitive Search index, the chatbot can perform vector or keyword searches over the extracted text, enabling it to retrieve relevant passages to answer user questions. This is the standard approach for grounding a custom chatbot on proprietary documents without modifying the underlying model.

Answer

Use Azure AI Document Intelligence to extract text from PDFs before indexing

Answer

Deploy Azure AI Content Safety to filter responses

Answer

Fine-tune the GPT model on the PDF content

Question 17

You are developing a content moderation solution that uses Azure Content Moderator to review images uploaded by users. The solution must flag images for potential adult content. Which TWO actions should you take to achieve this goal?

Accepted Answer

Configure a human review loop using the Review tool. Option C is correct because Azure Content Moderator's Review tool enables human-in-the-loop review, which is essential for accurately flagging adult content when automated confidence scores are borderline. This allows human moderators to confirm or override the automated classification, ensuring compliance with content policies. Option D is correct because the Evaluate operation on the image endpoint directly analyzes images for adult and racy content using pre-trained models, returning a confidence score that can trigger further action.

Answer

Train a custom image classifier using Content Moderator's training API

Answer

Use the List Management API to add images to a blocklist

Answer

Use the OCR operation to extract text from images

Question 18

Which TWO actions should you take to reduce the latency of an Azure AI Computer Vision OCR call on a large image?

Accepted Answer

Resize the image to a smaller resolution before calling the API.. Options B and D are correct. B: Resizing reduces processing time. D: Using the Read API asynchronously allows the client to poll, avoiding timeout. A: Increasing timeout doesn't reduce latency. C: Using CPU doesn't help. E: Cognitive Services container on-premises might add network latency.

Answer

Use a CPU-bound compute instance.

Answer

Increase the API timeout value.

Answer

Deploy the Cognitive Services container on-premises.

Question 19

Which TWO actions should you take to ensure compliance with data privacy regulations when using Azure AI Language to process customer support transcripts that contain personally identifiable information (PII)?

Accepted Answer

Enable PII detection and redaction in the Azure AI Language service.. Option D is correct because Azure AI Language's PII detection and redaction feature is specifically designed to identify and mask personally identifiable information (PII) in text, such as names, addresses, and social security numbers, directly within the service. This built-in capability ensures that sensitive data is removed or obfuscated before storage or further processing, directly supporting compliance with data privacy regulations like GDPR or HIPAA.

Answer

Disable diagnostic logging for the resource.

Answer

Use customer-managed keys (CMK) for encryption.

Answer

Apply Azure AI Content Safety filters to anonymize personal data.

Question 20

Which TWO actions are valid ways to authenticate to Azure AI services?

Accepted Answer

Use an API key.. Option B is correct because Azure AI services accept API keys as a straightforward authentication method. Each service generates a pair of keys that must be included in the `Ocp-Apim-Subscription-Key` header of HTTP requests. Option C is correct because Microsoft Entra ID (formerly Azure AD) authentication with a service principal is fully supported for Azure AI services, allowing token-based authentication via the `Authorization` header with a bearer token obtained from the Microsoft identity platform.

Answer

Use a client certificate.

Answer

Use a shared access signature (SAS) token.

Answer

Use a managed identity.