AI-102 Practice Test 4 — 25 Questions

Question 1

A company is using Azure Form Recognizer to extract data from invoices. The prebuilt model does not correctly extract a custom field that is specific to the company's invoices. What is the most appropriate action to improve extraction accuracy for this field?

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

Accepted Answer

Train a custom model using labeled invoices that include the custom field.. The prebuilt Form Recognizer model is designed for common invoice layouts and may not recognize company-specific fields. Training a custom model with labeled invoices that include the custom field allows the model to learn the field's location and semantics, significantly improving extraction accuracy for that specific field.

Answer

Use the prebuilt model with a custom field mapping.

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Adjust the confidence threshold for the prebuilt model.

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Retrain the prebuilt model with additional invoices.

Question 2

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.. 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.

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Lower the temperature parameter to 0.

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Add more examples to the prompt.

Question 3

A company is building a chatbot using Azure Bot Service and Language Understanding (LUIS). The chatbot needs to handle user intents for booking flights and checking flight status. After testing, the chatbot frequently fails to distinguish between the two intents when users mention flight numbers. Which action should the engineer take to improve intent recognition?

Accepted Answer

Add more utterances that include flight numbers to the training data for both intents.. Adding more utterances that include flight numbers to both intents provides LUIS with more varied examples of how flight numbers appear in natural language, enabling the model to learn distinguishing patterns. Without sufficient training data containing flight numbers, LUIS cannot reliably differentiate between 'BookFlight' and 'CheckFlightStatus' when users mention flight numbers, as the entity alone does not determine intent.

Answer

Increase the number of intents to split the flight-related queries further.

Answer

Reduce the confidence score threshold for intent detection.

Answer

Use the prebuilt domain for flight booking to improve accuracy.

Question 4

A company wants to extract key-value pairs from scanned invoices using Azure AI. Which service should they use?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) is the correct choice because it is specifically designed to extract key-value pairs, tables, and structured data from scanned documents like invoices. Unlike the Read API or OCR API, which only return raw text or OCR output, Document Intelligence uses prebuilt models (e.g., 'prebuilt-invoice') that understand the semantic layout of invoices, enabling direct extraction of fields such as invoice number, date, and total amount.

Answer

Read API

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Custom Vision

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OCR API

Question 5

You are building a solution to detect if a person is wearing a hard hat in construction site images. You have a small dataset of labeled images. Which Azure service should you use?

Accepted Answer

Azure Custom Vision. Azure Custom Vision is the correct choice because it allows you to train a custom image classification model with your own small dataset of labeled construction site images to detect whether a person is wearing a hard hat. Unlike pre-built services, Custom Vision specializes in fine-tuning models for specific visual concepts that are not covered by general-purpose APIs, making it ideal for niche object detection tasks like hard hat detection.

Answer

Azure AI Vision Image Analysis

Answer

Azure Video Indexer

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Azure AI Document Intelligence

Question 6

A manufacturing company uses Azure Custom Vision to detect defects on an assembly line. The model is deployed to a container on a local edge server. Recently, the model's accuracy dropped. You suspect data drift. What should you do to monitor and retrain the model?

Accepted Answer

Periodically collect new images with labels, retrain the model in Custom Vision, and redeploy the updated container.. Custom Vision models deployed to containers on edge devices do not expose a REST endpoint that Azure Machine Learning's data drift monitoring can directly access. The only way to detect drift and retrain is to periodically collect new labeled images from the production line, retrain the model in Custom Vision, and redeploy the updated container to the edge server.

Answer

Use Azure Machine Learning data drift monitoring on the Custom Vision endpoint.

Answer

Configure Custom Vision to send alerts when drift is detected.

Answer

Enable active learning in Custom Vision to automatically retrain the model.

Question 7

You are building a chatbot that must understand user intents from free-text input. You have a small set of labeled examples. Which Azure AI Language feature should you use to classify intents with minimal effort?

Accepted Answer

Conversational Language Understanding (CLU). Conversational Language Understanding (CLU) is the correct choice because it is specifically designed to extract intents and entities from free-text input in a conversational context, and it can be trained with a small set of labeled examples to classify user intents with minimal effort. CLU provides a pre-built pipeline for intent recognition and entity extraction, making it the most efficient option for building a chatbot that understands user intents.

Answer

Entity Linking

Answer

Custom Text Classification

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Language Detection

Question 8

A company wants to build a solution that can identify and redact personally identifiable information (PII) from customer support transcripts. The solution must handle multiple languages. Which Azure AI service should be used?

Accepted Answer

Azure AI Language - PII Detection. Azure AI Language's PII Detection feature is specifically designed to identify and redact personally identifiable information in text across multiple languages. It supports over 30 languages and can detect entities such as names, addresses, phone numbers, and credit card numbers, making it the correct choice for this multilingual PII redaction requirement.

Answer

Azure AI Content Safety

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Azure AI Document Intelligence

Answer

Azure AI Translator

Question 9

Which THREE factors are critical to consider when designing a custom vision solution for a manufacturing quality inspection system?

Accepted Answer

Imbalance between defective and non-defective product samples.. Class imbalance is a critical factor in custom vision solutions for manufacturing quality inspection. If defective samples are rare compared to non-defective ones, the model may become biased toward predicting the majority class, leading to poor recall for defects. Azure Custom Vision allows adjusting the probability threshold and using techniques like oversampling or weighted loss to mitigate this, but the imbalance must be accounted for during dataset preparation.

Answer

The need for optical character recognition (OCR) of product serial numbers.

Answer

Multilingual support for labeling.

Question 10

Your organization needs to monitor Azure AI services for unusual activity patterns that might indicate a security threat. Which Microsoft security solution should you use?

Accepted Answer

Microsoft Sentinel. Microsoft Sentinel is a cloud-native Security Information and Event Management (SIEM) and Security Orchestration Automated Response (SOAR) solution. It is specifically designed to ingest logs from Azure AI services, apply analytics to detect unusual activity patterns, and generate alerts for potential security threats, making it the correct choice for monitoring AI services for security anomalies.

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Microsoft Intune

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Microsoft Defender XDR

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Microsoft Purview

Question 11

Your organization is using Azure AI Search to index a large collection of PDF documents stored in Azure Blob Storage. The index currently returns search results, but users complain that the results are not relevant when they search using natural language phrases. You need to improve the relevance of search results without rewriting the application. What should you do?

Accepted Answer

Enable semantic search on the index and configure a semantic configuration.. Semantic search in Azure AI Search uses advanced language models to understand the intent behind natural language queries, re-ranking results based on semantic relevance rather than just keyword matching. Enabling semantic search and configuring a semantic configuration directly addresses the user complaint about poor relevance for natural language phrases without requiring application changes.

Answer

Increase the number of replicas for the search service to improve query performance.

Answer

Create a new index with a blob indexer that uses the 'content' field only.

Answer

Configure a custom analyzer on the index to handle stop words and synonyms.

Question 12

A manufacturing company uses Azure AI Custom Vision to detect defects on a production line. The model was trained with 500 images per class and achieves 95% accuracy. After deployment, the model's accuracy drops to 80% due to changes in lighting conditions. What is the most effective first step to improve the model's robustness?

Accepted Answer

Capture additional images under the new lighting and retrain the model.. The drop in accuracy is caused by a domain shift—specifically, new lighting conditions that were not represented in the original training set. The most effective first step is to capture additional images under the new lighting and retrain the model, as Custom Vision relies on diverse, representative training data to generalize to real-world variations. This directly addresses the root cause by expanding the training distribution to include the new lighting scenario, which is a fundamental principle of supervised learning in computer vision.

Answer

Reduce the probability threshold to increase recall.

Answer

Use Azure AutoML to automatically find the best algorithm.

Answer

Add more images from the original lighting conditions to the training set.

Question 13

Which TWO Azure AI services can be used to extract text from images and PDFs? (Select two.)

Accepted Answer

Azure AI Vision OCR. Azure AI Vision OCR (option C) is correct because its Read/OCR capability extracts printed and handwritten text directly from images and scanned documents. Azure AI Document Intelligence (option D) is correct because it uses prebuilt and custom models to extract text, key-value pairs, and tables from PDFs, images, and forms. Azure AI Translator (A) performs text translation, not optical character recognition, so it cannot extract text from images or PDFs. Azure AI Search (B) is a search indexing service that can consume extracted text but does not itself perform OCR on images or PDFs. Azure AI Language (E) provides NLP features such as sentiment analysis and entity recognition on existing text, not text extraction from images or PDFs.

Answer

Azure AI Translator

Answer

Azure AI Search

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Azure AI Language

Question 14

Which THREE factors should you consider when choosing between Azure AI Custom Vision and Azure AI Vision pre-built models for an image classification task? (Choose three.)

Accepted Answer

Availability of labeled training data specific to the domain. Azure AI Custom Vision is specifically designed for scenarios where you have domain-specific labeled training data that is not covered by pre-built models. Custom Vision allows you to upload your own labeled images and train a custom model tailored to your unique classification needs, which is essential when off-the-shelf models fail to recognize your target classes.

Answer

Image format support (JPEG, PNG)

Answer

Need for real-time inference latency

Question 15

Your company has a large repository of scanned invoices in PDF format. You need to extract invoice number, date, total amount, and vendor name from these PDFs. Which Azure AI service should you use?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) is purpose-built for extracting structured data (fields like invoice number, date, total amount, vendor name) from scanned documents such as invoices and receipts. It uses prebuilt models trained specifically on invoice layouts and supports both OCR and key-value pair extraction from PDFs.

Answer

Azure AI Language

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Azure AI Search

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Azure AI Vision

Question 16

You are troubleshooting an Azure AI Search indexer that fails to index a PDF file stored in Azure Blob Storage. The error message indicates that the document is encrypted. What is the most likely cause and solution?

Accepted Answer

The PDF is encrypted; remove encryption before indexing. The most likely cause is that the PDF is encrypted, and the solution is to remove encryption before indexing. Azure AI Search indexers cannot decrypt password-protected or encrypted PDFs; they require unencrypted content to extract text. Therefore, the file must be decrypted prior to indexing.

Answer

The indexer is not configured with the PDF parser; set the parsing mode

Answer

The file format is unsupported; convert to PDF/A

Answer

The file is too large; split it into smaller parts

Question 17

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 18

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

Answer

Set the temperature parameter to 0

Answer

Disable content filtering to allow more flexibility

Question 19

You run the above Azure CLI command. What is the expected output?

Accepted Answer

The primary and secondary keys. The Azure CLI command `az cognitiveservices account keys list` retrieves only the primary and secondary API keys for the Cognitive Services account. The endpoint is not included in the output; it must be obtained separately using `az cognitiveservices account show`. Therefore, the expected output contains the primary key and secondary key only.

Answer

The primary and secondary keys along with the endpoint

Answer

A list of endpoints for the service

Answer

An error because the command is incorrect

Question 20

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.

Answer

Azure Machine Learning and Azure Kubernetes Service

Answer

Azure AI Bot Service and Azure Functions

Answer

Azure AI Document Intelligence and Azure AI Translator