Microsoft Azure AI Fundamentals - AI-900 Exam Practice Test
You have an Azure Machine Learning model that uses clinical data to predict whether a patient has a disease.
You clean and transform the clinical data.
You need to ensure that the accuracy of the model can be proven.
What should you do next?
You clean and transform the clinical data.
You need to ensure that the accuracy of the model can be proven.
What should you do next?
Correct Answer: A
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You build a QnA Maker bot by using a frequently asked questions (FAQ) page.
You need to add professional greetings and other responses to make the bot more user friendly.
What should you do?
You need to add professional greetings and other responses to make the bot more user friendly.
What should you do?
Correct Answer: A
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To complete the sentence, select the appropriate option in the answer area.
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of regression machine learning", regression is a type of supervised machine learning used when the target variable (the value you want to predict) is a continuous numeric value.
In this scenario, the task is to predict how many hours of overtime a delivery person will work based on the number of orders received. Both the input (number of orders) and the output (hours of overtime) are numeric variables. Since the goal is to estimate a quantitative value rather than categorize or group data, this is a classic example of a regression problem.
Regression models analyze the relationship between variables to make numerical predictions. For example, the model might learn that each additional 20 orders increases overtime by about two hours. Common algorithms used for regression include linear regression, decision tree regression, and boosted regression models. These models produce outputs such as "expected overtime = 5.6 hours," which are continuous numeric results.
To contrast with the other options:
* Classification is used for predicting categories or labels, such as "overtime required" vs. "no overtime," or "high-risk" vs. "low-risk." It deals with discrete outputs rather than continuous numbers.
* Clustering is an unsupervised learning approach used to group similar data points based on shared characteristics, such as grouping delivery staff by performance patterns or customer types.
As emphasized in Microsoft's Responsible AI and Machine Learning Fundamentals learning paths, regression models are ideal for numeric forecasting problems such as predicting sales, revenue, demand, or working hours.
Therefore, the correct answer is: Regression.
Reference:Microsoft Learn - Identify the types of machine learning models: Regression, Classification, and Clustering (AI-900 Learning Path)
What are two metrics that you can use to evaluate a regression model? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
Correct Answer: D,E
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What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
Correct Answer: A,B
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For each of The following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
The Azure AI Language service (part of Azure Cognitive Services) provides a set of natural language processing (NLP) capabilities designed to analyze and interpret text data. Its core features include language detection, key phrase extraction, sentiment analysis, and named entity recognition (NER).
* Language Identification - YESAccording to the Microsoft Learn module "Analyze text with Azure AI Language," one of the service's built-in capabilities is language detection, which determines the language of a given text string (e.g., English, Spanish, or French). This allows applications to automatically adapt to multilingual input.
* Handwritten Signature Detection - NOThe Azure AI Language service only processes text-based data; it does not analyze images or handwriting. Detecting handwritten signatures requires computer vision capabilities, specifically Azure AI Vision or Azure AI Document Intelligence, which can extract and interpret visual content from scanned documents or images.
* Identifying Companies and Organizations - YESThe Named Entity Recognition (NER) feature within Azure AI Language can identify entities such as people, locations, dates, organizations, and companies mentioned in text. It tags these entities with categories, enabling structured analysis of unstructured data.
# Summary:
* Language detection # Yes (supported by AI Language).
* Handwritten signatures # No (requires Computer Vision).
* Entity recognition for companies/organizations # Yes (supported by AI Language NER).
Select the answer that correctly completes the sentence.
Correct Answer:
Explanation:
In the Microsoft Azure AI Fundamentals (AI-900) curriculum, computer vision capabilities refer to artificial intelligence systems that can analyze and interpret visual content such as images and videos. The Azure AI Vision and Face API services provide pretrained models for detecting, recognizing, and analyzing visual information, enabling developers to build intelligent applications that understand what they " see. " When asked how computer vision capabilities can be deployed, the correct answer is to integrate a face detection feature into an app. This aligns with Microsoft Learn's module "Describe features of computer vision workloads," which explains that computer vision can identify objects, classify images, detect faces, and extract text (OCR). The Face API, a part of Azure AI Vision, specifically provides face detection, verification, and emotion recognition capabilities.
Integrating these services into an application allows it to perform actions such as:
* Detecting human faces in photos or video streams.
* Recognizing facial attributes like age, emotion, or head pose.
* Enabling secure authentication based on face recognition.
The other options are incorrect because they relate to different AI workloads:
* Develop a text-based chatbot for a website: This falls under Conversational AI, implemented with Azure Bot Service or Conversational Language Understanding (CLU).
* Identify anomalous customer behavior on an online store: This task relates to machine learning and anomaly detection models, not computer vision.
* Suggest automated responses to incoming email: This uses Natural Language Processing (NLP) capabilities, not visual analysis.
Therefore, the correct and Microsoft-verified completion of the statement is:
"Computer vision capabilities can be deployed to integrate a face detection feature into an app."
You ate building a Conversational Language Understanding model for an e-commerce business.
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?
Correct Answer: A
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You are processing photos of runners in a race.
You need to read the numbers on the runners' shirts to identity the runners in the photos.
Which type of computer vision should you use?
You need to read the numbers on the runners' shirts to identity the runners in the photos.
Which type of computer vision should you use?
Correct Answer: A
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Which type of Azure Al workload should you use to create illustrations based on the text of an article?
Correct Answer: B
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For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
The Translator service, part of Microsoft Azure Cognitive Services, is designed specifically for text translation between multiple languages. It is a cloud-based neural machine translation service that supports more than 100 languages. According to Microsoft Learn's module "Translate text with the Translator service", this service provides two main capabilities: text translation and automatic language detection.
* "You can use the Translator service to translate text between languages." # YesThis statement is true.
The primary purpose of the Translator service is to translate text accurately and efficiently between supported languages, such as English to Spanish or French to Japanese. It maintains contextual meaning using neural machine translation models.
* "You can use the Translator service to detect the language of a given text." # YesThis statement is also true. The Translator service includes automatic language detection, which determines the source language before translation. For instance, if a user submits text in an unknown language, the service can identify it automatically before performing translation.
* "You can use the Translator service to transcribe audible speech into text." # NoThis statement is false.
Transcribing speech (audio) into text is a function of the Azure Speech service, specifically the Speech- to-Text API, not the Translator service.
Therefore, the Translator service is used for text translation and language detection, while speech transcription belongs to the Speech service.
You plan to use Azure Cognitive Services to develop a voice controlled personal assistant app.
Match the Azure Cognitive Services to the appropriate tasks.
To answer, drag the appropriate service from the column on the left to its description on the right Each service may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Match the Azure Cognitive Services to the appropriate tasks.
To answer, drag the appropriate service from the column on the left to its description on the right Each service may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn Cognitive Services documentation, developing a voice-controlled personal assistant app involves integrating multiple Azure AI services that specialize in different aspects of language and speech processing. The three services in focus-Azure AI Speech, Azure AI Language Service, and Azure AI Translator Text-perform unique but complementary roles in conversational AI systems.
* Convert a user's speech to text # Azure AI SpeechThe Azure AI Speech service provides speech-to-text (STT) capabilities. It enables applications to recognize spoken language and convert it into written text in real time. This is often the first step in voice-enabled applications, transforming audio input into a machine-readable format that can be analyzed further.
* Identify a user's intent # Azure AI Language serviceOnce speech has been transcribed, the Azure AI Language service (which includes capabilities like Conversational Language Understanding and Text Analytics) interprets the meaning of the text. It detects the user's intent (what the user wants to accomplish) and extracts entities (key data points) from the input. This service helps the assistant understand commands like "Book a flight" or "Set a reminder."
* Provide a spoken response to the user # Azure AI SpeechAfter determining an appropriate response, the system uses the text-to-speech (TTS) feature of Azure AI Speech to convert the assistant's text-based reply back into natural-sounding spoken language, allowing the user to hear the response.
Together, these services form the backbone of a conversational AI system: Speech-to-Text # Language Understanding # Text-to-Speech, aligning precisely with the AI-900 curriculum's explanation of how Azure Cognitive Services enable intelligent voice-based interactions.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
The correct answers are Yes, Yes, and Yes.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn content in the section "Describe features of conversational AI workloads on Azure", bots created using Azure Bot Service can interact with users across multiple channels. The AI-900 syllabus explains that Azure Bot Service integrates with various communication platforms, allowing developers to build a single bot that can be deployed in many contexts without rewriting the logic.
* "You can communicate with a bot by using Cortana." - Yes.The AI-900 learning materials explain that Cortana, Microsoft's intelligent personal assistant, can serve as a channel for bots built with the Azure Bot Service. Through the Bot Framework, bots can be connected to Cortana to allow users to interact via voice or text. Although Cortana is less prominent now, it remains conceptually included in the AI-
900 coverage as an example of a voice-based conversational AI channel.
* "You can communicate with a bot by using Microsoft Teams." - Yes.This statement is true and directly referenced in the AI-900 syllabus. Microsoft Teams is a fully supported communication channel for Azure Bot Service. Bots in Teams can handle chat messages, commands, and interactions in team or personal contexts. The Microsoft Learn materials specify Teams as one of the native connectors where enterprise users can interact with organizational bots.
* "You can communicate with a bot by using a webchat interface." - Yes.This is also true. The Web Chat channel is one of the most common ways to deploy bots publicly. Azure Bot Service provides a Web Chat control that can be embedded directly into a webpage or web application. This allows users to interact with the bot using a chat window, just like on customer service websites.
Therefore, all three interfaces-Cortana (voice-based), Microsoft Teams (enterprise chat), and Web Chat (browser-based)-are valid and officially supported communication channels for Azure bots.
What should you do to ensure that an Azure OpenAI model generates accurate responses that include recent events?
Correct Answer: C
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