AI-102 Practice Test 33 — 15 Questions

Question 1

A company uses Azure AI Language's custom text classification to categorize support tickets. The model was trained with 5000 labeled examples and achieves 90% accuracy. However, for a specific category (e.g., 'billing'), the model frequently misclassifies tickets that contain both billing and technical issues. Which action should you take to improve classification for this category?

Accepted Answer

Add more labeled examples for the 'billing' category, especially those that are mixed with other categories.. Option B is correct because adding more labeled examples for the 'billing' category, especially those that are mixed with other categories, will help the model learn to distinguish them better. Option A is wrong because reducing the number of categories may not address the specific confusion. Option C is wrong because increasing the training epochs may lead to overfitting. Option D is wrong because using a different algorithm is not an option in Azure AI Language's custom text classification.

Answer

Reduce the number of categories to simplify the classification.

Answer

Increase the number of training epochs to further train the model.

Answer

Use a different classification algorithm, such as a neural network.

Question 2

Your company uses Azure AI Document Intelligence to process invoices. You need to extract the invoice date and total amount. Which model should you use?

Accepted Answer

Prebuilt invoice model. The prebuilt invoice model is specifically trained to extract fields like invoice date and total amount from invoices. The layout model extracts text and tables, not specific fields; the general document model is for key-value pairs; the read model only extracts text.

Answer

Read model

Answer

Layout model

Answer

General document model

Question 3

You are developing a conversational agent using Microsoft Copilot Studio that must handle complex multi-turn conversations. The agent needs to maintain context across multiple user inputs. Which feature should you use?

Accepted Answer

Use topics with slots to collect information across turns.. Option B is correct because Copilot Studio uses topics with slots to manage context and gather information across turns. Option A is wrong because entities alone don't manage conversation flow. Option C is wrong because variables are used to store data but slots are for context. Option D is wrong because actions are for API calls, not conversation management.

Answer

Use actions to call external APIs for context.

Answer

Use global variables to store conversation state.

Answer

Use entities to capture user input.

Question 4

Refer to the exhibit. You are defining a custom entity recognition model in Azure AI Language. The exhibit shows a partial configuration. What is the relationship between 'Laptop' and 'Electronics'?

Accepted Answer

Laptop is a type of Electronics.. Option A is correct. The relation type 'InstanceOf' indicates that Laptop is an instance of (i.e., a type of) Electronics. Option B is wrong because Laptop is not a part of Electronics in the model. Option C is wrong because the relation is not 'HasPart'. Option D is wrong because the relation is defined.

Answer

There is no defined relationship.

Answer

Electronics is a type of Laptop.

Answer

Laptop is a part of Electronics.

Question 5

You are using Azure AI Language to analyze customer reviews. You need to determine whether each review expresses a positive, negative, or neutral sentiment. Which API should you call?

Accepted Answer

Sentiment analysis API.. Option B is correct because the sentiment analysis API in Azure AI Language returns sentiment labels (positive, negative, neutral) and confidence scores. Option A is wrong because the language detection API detects language. Option C is wrong because the entity recognition API extracts entities. Option D is wrong because the key phrase extraction API extracts key phrases.

Answer

Language detection API.

Answer

Entity recognition API.

Answer

Key phrase extraction API.

Question 6

A legal firm uses Azure AI Language's custom NER to extract party names, dates, and clauses from contracts. The model performs well on English contracts but poorly on French contracts. The firm wants to improve performance without retraining from scratch. What is the most efficient approach?

Accepted Answer

Use the multilingual option in Azure AI Language custom NER to extend the existing project to include French.. Option D is correct because Azure AI Language supports multilingual projects that can learn from pre-existing English data and transfer to French. Option A is wrong because it requires separate management. Option B is wrong because translation may lose legal nuances. Option C is wrong because Translator adds latency and cost.

Answer

Create a separate custom NER project for French and train from scratch using French contracts.

Answer

Retrain the English model with a mix of English and French contracts.

Answer

Use Azure AI Translator to translate French contracts to English, then use the English model.

Question 7

Refer to the exhibit. You submit this request to Azure AI Language's conversational language understanding (CLU) for the 'FlightBooking' project. The model correctly identifies the intent as 'BookFlight' and extracts entities: 'Seattle' as FromCity, 'New York' as ToCity, and 'June 15th' as Date. What is the next step for the application?

Accepted Answer

Call a separate booking API with the extracted entities to complete the reservation.. Option B is correct. After CLU extracts intent and entities, the application must call a booking API to complete the action. Option A is wrong because the CLU model does not perform actions. Option C is wrong because the response already contains the entities. Option D is wrong because the intent is already identified.

Answer

Use the CLU response to directly book the flight via the Azure AI Language service.

Answer

Prompt the user to rephrase the request because the intent is ambiguous.

Answer

Send another request to CLU to confirm the booking details.

Question 8

Which TWO actions should you take to improve the performance of a custom named entity recognition (NER) model in Azure AI Language?

Accepted Answer

Use a balanced dataset with similar numbers of examples for each entity.. Options A and C are correct because labeling more examples with entity annotations provides more training data, and using a balanced dataset helps the model learn all entities equally. Option B is wrong because increasing the training time is not a user-controlled parameter in Azure AI Language. Option D is wrong because using only prebuilt entities does not improve a custom model. Option E is wrong because reducing the number of entities may lose needed information.

Answer

Increase the training time of the model.

Answer

Reduce the number of entity types to simplify the model.

Answer

Use only prebuilt entity types to avoid training from scratch.

Question 9

A company deploys a custom question answering project in Azure AI Language. Users report that the bot sometimes returns irrelevant answers. The knowledge base contains hundreds of QnA pairs. You need to improve answer relevance without retraining the model. What should you do?

Accepted Answer

Add alternate phrases to existing QnA pairs for common user queries.. Option B is correct because adding alternate questions to existing QnA pairs improves the model's ability to match user queries without retraining. Option A is wrong because increasing the confidence score threshold may cause many legitimate queries to go unanswered. Option C is wrong because enabling active learning requires user feedback and does not immediately improve relevance. Option D is wrong because reducing the number of QnA pairs may remove valid content.

Answer

Increase the confidence score threshold in the project settings.

Answer

Reduce the number of QnA pairs to decrease ambiguity.

Answer

Enable active learning to let the bot suggest new questions based on user queries.

Question 10

Which THREE components are required to deploy a bot using Azure AI Language's conversational language understanding (CLU) and Azure Bot Service?

Accepted Answer

An Azure Bot Service bot with the CLU model as a skill.. Options A, C, and E are correct because a CLU project provides the language model, an Azure Bot Service bot handles the bot logic and channels, and a Microsoft Entra ID app registration is needed for authentication. Option B is wrong because a Translator resource is not required for CLU. Option D is wrong because a QnA Maker resource is not required (CLU handles both intents and entities).

Answer

A QnA Maker resource for FAQs.

Answer

A Translator resource for multilingual support.

Question 11

A company uses Azure AI Language Service for custom text classification. The model is trained to classify support tickets into categories. After deployment, the model performs well on the test set but poorly on new incoming tickets. Which action should be taken to improve generalization?

Accepted Answer

Add more labeled data from actual production tickets. The correct answer is C because adding more diverse training data from production helps the model generalize. A (increasing the number of training epochs) may lead to overfitting. B (reducing the confidence threshold) does not address generalization. D (using a prebuilt model) may not fit the custom categories.

Answer

Switch to a prebuilt text classification model

Answer

Increase the number of training epochs

Answer

Reduce the confidence threshold for classification

Question 12

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. Option C is correct because Azure AI Language's PII detection and redaction supports multiple languages. Option A is wrong because Azure AI Content Safety is for harmful content. Option B is wrong because Document Intelligence is for forms. Option D is wrong because Azure AI Translator is for translation.

Answer

Azure AI Content Safety

Answer

Azure AI Document Intelligence

Answer

Azure AI Translator

Question 13

You are building a chatbot that uses Azure AI Language to extract intents and entities from user utterances. The bot must recognize custom entities like product names that are not in the default model. Which feature should you use?

Accepted Answer

Custom named entity recognition (NER) component.. Option C is correct because a custom named entity recognition (NER) component allows you to train a model to extract custom entities. Option A is wrong because the prebuilt entity recognition only recognizes common entities. Option B is wrong because a list entity in a conversational language understanding (CLU) project is for matching exact terms, not for training a model. Option D is wrong because key phrase extraction does not extract entities.

Answer

Prebuilt entity recognition component.

Answer

Key phrase extraction.

Answer

List entity in a conversational language understanding (CLU) project.

Question 14

Which TWO features are available in Azure AI Language's extractive summarization?

Accepted Answer

Confidence scores for each extracted sentence.. Options A and E are correct because extractive summarization returns a ranked list of sentences and a confidence score for each sentence. Option B is wrong because it does not generate new sentences. Option C is wrong because it does not categorize sentences by sentiment. Option D is wrong because it does not identify named entities; that's entity recognition.

Answer

Identified named entities from the document.

Answer

Sentiment scores for each extracted sentence.

Answer

Generated abstractive summary.

Question 15

A company needs to extract personally identifiable information (PII) from customer support transcripts stored in Azure Blob Storage. Which Azure AI service should they use?

Accepted Answer

Azure AI Language Service. The correct answer is B because Azure AI Language Service includes PII detection. A (Azure AI Vision) handles images, not text. C (Azure AI Speech) handles audio. D (Azure AI Translator) translates text.

Answer

Azure AI Speech

Answer

Azure AI Translator

Answer

Azure AI Vision