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Azure AI-900 study materials
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Azure AI-900 practice questions

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Question 1Describe Artificial Intelligence workloads and considerations

A company receives thousands of scanned purchase orders and wants key fields such as vendor name and total amount extracted automatically. Which AI workload should it use?

  1. Object detection in computer vision
  2. Document intelligence Correct answer.
  3. Anomaly detection
  4. Speech synthesis

Explanation

Document intelligence combines optical character recognition with trained models to extract structured fields, key-value pairs, and tables from forms and scanned documents. It is purpose-built for turning semi-structured paperwork into usable data.

Question 2Describe Artificial Intelligence workloads and considerations

Which responsible AI principle focuses on ensuring an AI system operates consistently and safely under both expected and unexpected conditions?

  1. Reliability and safety Correct answer.
  2. Accountability
  3. Transparency
  4. Inclusiveness

Explanation

The reliability and safety principle requires that AI systems perform as intended, handle unexpected inputs gracefully, and include safeguards against harmful outcomes. Transparency, inclusiveness, and accountability address different concerns such as understanding, accessibility, and ownership.

Question 3Describe Artificial Intelligence workloads and considerations

Which AI workload converts a recording of a customer phone call into a written transcript?

  1. Sentiment analysis
  2. Text-to-speech
  3. Speech recognition Correct answer.
  4. Machine translation

Explanation

Speech recognition, also called speech-to-text, transcribes spoken audio into written text. The reverse direction, generating audio from text, is text-to-speech.

Question 4Describe Artificial Intelligence workloads and considerations

Which responsible AI principle requires that an AI system treat people in similar circumstances in a similar way, regardless of demographic group?

  1. Accountability
  2. Inclusiveness
  3. Transparency
  4. Fairness Correct answer.

Explanation

Fairness means AI systems should not produce biased outcomes or discriminate against particular groups. It is measured by comparing model behavior and results across subgroups of people.

Question 5Describe Artificial Intelligence workloads and considerations

Which machine learning task predicts a numeric value, such as the expected selling price of a house?

  1. Anomaly detection
  2. Regression Correct answer.
  3. Clustering
  4. Classification

Explanation

Regression models learn to output a continuous numeric value from input features, such as a price, temperature, or demand quantity. Classification instead predicts a category label.

Question 6Describe Artificial Intelligence workloads and considerations

Which machine learning approach groups customers with similar purchasing behavior when no labels are available?

  1. Anomaly detection
  2. Regression
  3. Classification
  4. Clustering Correct answer.

Explanation

Clustering is an unsupervised technique that discovers natural groupings in data without predefined labels. The resulting groups are inferred from similarity between data points.

Question 7Describe Artificial Intelligence workloads and considerations

Which AI workload is used to flag unusual credit card transactions that differ from a customer's normal spending pattern?

  1. Anomaly detection Correct answer.
  2. Clustering
  3. Image classification
  4. Regression

Explanation

Anomaly detection identifies data points that deviate significantly from expected patterns, which makes it well suited to fraud and fault detection. It can work with few or no labeled examples of the unusual event.

Question 8Describe Artificial Intelligence workloads and considerations

Which AI workload lets a user ask questions and receive answers across several turns of dialogue with a software agent?

  1. Computer vision
  2. Conversational AI Correct answer.
  3. Knowledge mining
  4. Speech synthesis

Explanation

Conversational AI covers bots and agents that maintain a dialogue with a user, interpreting intent over multiple turns and responding appropriately. It often combines language understanding with a channel such as chat, voice, or messaging.

Question 9Describe Artificial Intelligence workloads and considerations

An organization wants employees to search a large archive of scanned contracts and internal reports using natural language and receive answers with links to the source documents. Which AI workload fits best?

  1. Speech recognition
  2. Knowledge mining Correct answer.
  3. Regression modeling
  4. Anomaly detection

Explanation

Knowledge mining uses OCR, enrichment, and search indexing to make large unstructured document stores queryable in natural language. It typically returns answers together with references back to the underlying documents.

Question 10Describe Artificial Intelligence workloads and considerations

Which description best matches the transparency principle of responsible AI?

  1. Every AI system must support every spoken language used by any of its potential users.
  2. Users can understand how a system works and its limitations. Correct answer.
  3. Every AI system must encrypt all of its data at rest and in transit at all times.
  4. Every AI system must be verified as completely error-free before it is released to production.

Explanation

Transparency means the behavior of an AI system, and the boundaries of what it can reliably do, should be understandable to the people who use and are affected by it. Documentation, explanations, and clear communication of limitations are typical practices.

Question 11Describe Artificial Intelligence workloads and considerations

A bank has years of historical loan records labeled as 'repaid' or 'defaulted' and wants a model that predicts the label for new applicants. Which approach should be used?

  1. Reinforcement learning that rewards an agent for good decisions
  2. Supervised learning trained on labeled historical examples Correct answer.
  3. Unsupervised learning that groups similar applications without using labels
  4. A static rule set written entirely by hand

Explanation

When historical data already contains the correct answer for each case, supervised learning can map input features to those known labels. This is a binary classification problem because there are exactly two possible labels.

Question 12Describe Artificial Intelligence workloads and considerations

A speech recognition service performs well for most users but frequently fails for people with strong regional accents. Which responsible AI principle is most directly unmet?

  1. Inclusiveness Correct answer.
  2. Transparency
  3. Accountability
  4. Reliability and safety

Explanation

Inclusiveness requires AI systems to work well for people with diverse abilities, backgrounds, and characteristics, including different speech patterns. A service that only serves a subset of users fails that goal.

Question 13Describe Artificial Intelligence workloads and considerations

Which responsible AI principle places responsibility on the people who build and operate an AI system for the outcomes it produces?

  1. Transparency
  2. Privacy and security
  3. Fairness
  4. Accountability Correct answer.

Explanation

Accountability means humans remain responsible for AI systems and their effects, with clear ownership, oversight, and governance. It is why organizations define review processes and sign-off roles for AI solutions.

Question 14Describe Artificial Intelligence workloads and considerations

A manufacturer wants a system that finds and locates cracks in photographs of metal parts. Which AI workload should be used?

  1. Computer vision Correct answer.
  2. Text analytics
  3. Speech synthesis
  4. Natural language processing

Explanation

Computer vision models interpret images, and object detection within computer vision can both locate and classify visual defects. The input is photographic, so the visual workload applies rather than a language workload.

Question 15Describe Artificial Intelligence workloads and considerations

A company wants to automatically identify the main topics discussed in thousands of free-text customer reviews. Which workload applies?

  1. Anomaly detection in numeric records
  2. Natural language processing Correct answer.
  3. Computer vision image processing
  4. Text-to-speech synthesis

Explanation

Natural language processing extracts meaning from written text, including key phrases, topics, sentiment, and entities. Topic discovery from free-text reviews is a classic NLP scenario.

Question 16Describe Artificial Intelligence workloads and considerations

A demand forecasting model trained on 2019 data performs poorly after a sudden change in buying habits. What is the most likely cause?

  1. Overfitting to the training set
  2. Data drift in the input data Correct answer.
  3. Using too few input features
  4. Applying regularization too strongly

Explanation

Data drift occurs when the statistical properties of real-world inputs change after training, so patterns the model learned no longer hold. Retraining on recent data is the usual remedy.

Question 17Describe Artificial Intelligence workloads and considerations

Which scenario is the best fit for reinforcement learning?

  1. Grouping news articles by topic without any labels
  2. Transcribing a recorded meeting into written text
  3. Predicting house prices from a large set of labeled historical sales records
  4. A robot learning maze navigation through trial and reward Correct answer.

Explanation

Reinforcement learning trains an agent to take actions in an environment so as to maximize a reward signal, which suits sequential decision problems such as navigation. Labeled-example problems instead call for supervised learning.

Question 18Describe Artificial Intelligence workloads and considerations

A team must limit how much personal data an AI system collects and how long it retains that data. Which responsible AI principle does this address?

  1. Fairness
  2. Transparency
  3. Inclusiveness
  4. Privacy and security Correct answer.

Explanation

Privacy and security covers collecting only necessary personal data, protecting it, and retaining it no longer than required. This includes controls such as encryption, access restrictions, and data minimization.

Question 19Describe Artificial Intelligence workloads and considerations

Which AI workload generates spoken announcements from written text in a self-service phone system?

  1. Key phrase extraction
  2. Speech-to-text
  3. Machine translation
  4. Text-to-speech Correct answer.

Explanation

Text-to-speech synthesis converts written text into audible speech. It is the counterpart of speech-to-text, which converts audio into written words.

Question 20Describe Artificial Intelligence workloads and considerations

Which statement correctly describes the relationship among AI, machine learning, and deep learning?

  1. The three terms describe unrelated disciplines with no overlap in practice.
  2. Machine learning is a superset of AI and also includes deep learning as a subset.
  3. AI contains machine learning, which in turn contains deep learning. Correct answer.
  4. Deep learning is the broadest of the three terms and includes every AI system.

Explanation

Artificial intelligence is the broad field of building systems that exhibit intelligent behavior. Machine learning is a subset of AI that learns from data, and deep learning is a further subset of machine learning based on multi-layer neural networks.

Question 21Describe Artificial Intelligence workloads and considerations

A pneumonia detection model reports 99% accuracy on a test set in which 99% of the images are healthy. Which conclusion is most justified?

  1. The data is imbalanced, so accuracy can hide poor detection of the minority class. Correct answer.
  2. The model is ready for clinical use because its accuracy is above the 95% threshold commonly required.
  3. The model has almost certainly overfitted the training data and must be retrained from scratch.
  4. Accuracy is a trustworthy metric in this case because the test set contains a large number of images.

Explanation

With severe class imbalance, a model that always predicts the majority class can reach very high accuracy while never identifying a positive case. Metrics such as recall and precision for the minority class reveal the real performance.

Question 22Describe Artificial Intelligence workloads and considerations

An audit finds that a resume-screening model recommends fewer interviews for one demographic group. Which action best follows the fairness principle?

  1. Measure model outcomes across groups and remediate the disparity before deployment. Correct answer.
  2. Remove candidate names from the input data and deploy the model without further analysis.
  3. Lower the decision threshold so that a greater number of candidates pass the screening stage.
  4. Collect a much larger number of resumes so the training set becomes larger overall.

Explanation

Fairness requires measuring outcomes across subgroups and actively correcting disparities, for example through data remediation, feature changes, or threshold adjustments validated per group. Removing one sensitive field or simply enlarging the dataset does not confirm that the disparity is gone.

Question 23Describe Artificial Intelligence workloads and considerations

A team improves a hiring model's overall accuracy, but its outcomes become less equal across groups. What does this best illustrate?

  1. The model should be retrained repeatedly until both accuracy and fairness reach perfect scores.
  2. Accuracy and fairness can conflict, so teams must evaluate trade-offs. Correct answer.
  3. Accuracy is the only metric that matters when judging whether an AI system is responsible.
  4. Fairness always improves whenever a model's overall accuracy increases, so no further work is needed.

Explanation

Responsible AI involves balancing competing objectives, and optimizing one metric can degrade another such as fairness across groups. Teams therefore track multiple metrics and make deliberate, documented trade-off decisions.

Question 24Describe Artificial Intelligence workloads and considerations

Which statement distinguishes classification from clustering?

  1. Classification requires no training data at all, while clustering always needs a fully labeled dataset.
  2. Classification uses predefined labels; clustering discovers groups in unlabeled data. Correct answer.
  3. The two terms name the same machine learning task, differing only in the file format of the data.
  4. Clustering is used to predict numeric values, while classification is used to predict discrete categories.

Explanation

Classification is supervised and learns from examples that already carry the correct label, so the categories are known in advance. Clustering is unsupervised and infers groupings from similarity without any labels.

Question 25Describe Artificial Intelligence workloads and considerations

Why is a purely rule-based system often unsuitable for tasks such as recognizing objects in photographs?

  1. Rule-based systems cannot be deployed on a web server or in a cloud environment without modification.
  2. Rules cannot generalize from examples and must be rewritten as conditions change. Correct answer.
  3. Rule-based systems require large labeled training datasets before any rule can be evaluated.
  4. Rule-based systems always output numeric values, so they cannot be used for categorization tasks.

Explanation

Hand-written rules must anticipate every case explicitly and do not learn patterns from data, which makes them brittle for complex perceptual tasks. Machine learning models instead generalize from examples and adapt when retrained on new data.

Question 26Describe Artificial Intelligence workloads and considerations

A company wants software to read the printed text on millions of scanned receipts and store that text in a searchable database. Which AI workload provides this capability?

  1. Computer vision Correct answer.
  2. Natural language processing
  3. Speech recognition
  4. Anomaly detection

Explanation

Reading characters from a scanned image is optical character recognition, which is a computer vision capability that interprets pixels in an image. Natural language processing begins only after the text already exists in a machine-readable form.

Question 27Describe Artificial Intelligence workloads and considerations

A team building a self-driving shuttle must ensure that the system behaves predictably and does not cause harm when a sensor returns missing or unusual readings. Which responsible AI principle does this requirement describe?

  1. Reliability and safety Correct answer.
  2. Transparency of decisions
  3. Accountability for outcomes
  4. Privacy and security of data

Explanation

Reliability and safety requires that an AI system perform consistently and fail safely when it encounters conditions outside its normal operating range. Continuing to operate without harm when sensor input is imperfect is the defining concern of this principle.

Question 28Describe Artificial Intelligence workloads and considerations

A model is trained to predict the selling price of a house in dollars from its size, age, and location. Which type of machine learning task is this?

  1. Binary classification
  2. Clustering
  3. Reinforcement learning
  4. Regression Correct answer.

Explanation

Regression models predict a continuous numeric quantity, and a price in dollars is continuous. Classification would instead predict a discrete category, and clustering would group similar records without a target value.

Question 29Describe Artificial Intelligence workloads and considerations

A media company wants to generate searchable written transcripts from hundreds of hours of recorded interviews. Which AI workload should it use?

  1. Speech recognition Correct answer.
  2. Anomaly detection
  3. Text-to-speech synthesis
  4. Computer vision

Explanation

Speech recognition transcribes spoken audio into written text, which is exactly what producing transcripts from recordings requires. Text-to-speech works in the opposite direction, turning text into audio.

Question 30Describe Artificial Intelligence workloads and considerations

An accounts payable team receives thousands of scanned invoices with varying layouts and needs the vendor name, invoice date, and total amount captured automatically. Which AI workload is designed for this?

  1. Knowledge mining
  2. Generative AI
  3. Anomaly detection
  4. Document intelligence Correct answer.

Explanation

Document intelligence extracts structured fields such as names, dates, and totals from forms and invoices, including documents with differing layouts. It returns field-level values rather than a searchable index or newly generated content.

Question 31Describe Artificial Intelligence workloads and considerations

Which AI workload responds to a natural-language prompt by producing original content such as a paragraph of text or an illustration?

  1. Anomaly detection
  2. Computer vision
  3. Speech synthesis
  4. Generative AI Correct answer.

Explanation

Generative AI models create new content, including text and images, in response to a prompt. The other workloads analyze, classify, or convert existing data rather than create original output.

Question 32Describe Artificial Intelligence workloads and considerations

In supervised machine learning, what is the term for the measurable input attributes, such as age and income, that a model uses to make a prediction?

  1. Hyperparameters
  2. Features Correct answer.
  3. Labels
  4. Evaluation metrics

Explanation

Features are the input variables that describe each observation and drive the prediction, while the label is the known target value the model is trained to output. Hyperparameters and metrics relate to how a model is configured and scored, not to its input attributes.

Question 33Describe Artificial Intelligence workloads and considerations

A public self-service kiosk is designed so that people with visual impairments can complete every task using audio prompts and screen-reader support. Which responsible AI principle does this best demonstrate?

  1. Inclusiveness Correct answer.
  2. Transparency
  3. Reliability and safety
  4. Accountability

Explanation

Inclusiveness requires that AI systems empower and engage everyone, including people with disabilities, by offering usable alternative modes of interaction. Providing audio and screen-reader paths so all users can finish tasks is a direct application of that principle.

Question 34Describe Artificial Intelligence workloads and considerations

Which natural language processing capability classifies a piece of text as positive, negative, or neutral?

  1. Key phrase extraction
  2. Speech synthesis
  3. Sentiment analysis Correct answer.
  4. Object detection

Explanation

Sentiment analysis scores text for the attitude it expresses, commonly positive, negative, or neutral. Key phrase extraction instead returns the main terms in the text without judging opinion.

Question 35Describe Artificial Intelligence workloads and considerations

A subscription service trains a model that outputs a probability between 0 and 1 indicating whether each customer will cancel in the next month. Which type of machine learning task is this?

  1. Reinforcement learning
  2. Binary classification Correct answer.
  3. Regression
  4. Clustering

Explanation

The model chooses between two discrete outcomes, will cancel or will not cancel, which makes it binary classification; the probability is simply a confidence score for one of those classes. Regression would apply only if the target were a continuous quantity such as a revenue amount.

Question 36Describe Artificial Intelligence workloads and considerations

A drone must assign a class label to every individual pixel in each camera frame so that roads, trees, and buildings are each outlined. Which computer vision capability is required?

  1. Object detection
  2. Semantic segmentation Correct answer.
  3. Image classification
  4. Optical character recognition

Explanation

Semantic segmentation classifies each pixel, producing a mask that outlines the region belonging to every class. Image classification returns a single label for the whole picture, and object detection returns bounding boxes rather than pixel-level masks.

Question 37Describe Artificial Intelligence workloads and considerations

Which statement best describes what distinguishes deep learning from classical machine learning?

  1. It requires labeled training data, whereas classical methods do not
  2. It always produces models that are simpler to explain than classical ones
  3. It learns features automatically with deep neural networks Correct answer.
  4. It can be applied only to image data, while classical methods handle text

Explanation

Deep learning uses neural networks with many layers that learn increasingly abstract feature representations directly from raw data, reducing the need for hand-crafted features. Classical machine learning typically depends on features that a person defines in advance.

Question 38Describe Artificial Intelligence workloads and considerations

A live event requires spoken English to appear as written French subtitles within a few seconds. Which combination of AI capabilities is required?

  1. Speech synthesis and image classification
  2. Sentiment analysis and text translation
  3. Speech synthesis and optical character recognition
  4. Speech recognition and text translation Correct answer.

Explanation

The audio must first be transcribed into text by speech recognition, and that text is then translated into French by a text translation capability. Each stage transforms the content into the input format that the next stage requires.

Question 39Describe fundamental principles of machine learning on Azure

A data scientist trains a model by providing historical sales records that include the actual sales amount for each month. Which type of machine learning does this describe?

  1. Reinforcement learning
  2. Unsupervised learning
  3. Supervised learning Correct answer.
  4. Clustering analysis

Explanation

Supervised learning trains a model on examples that include both input features and the known outcome, called the label. Because historical sales amounts are supplied, the model can learn the mapping from inputs to the numeric outcome. Unsupervised methods work without labels.

Question 40Describe fundamental principles of machine learning on Azure

In a dataset used to train a model that predicts house prices, what is the term for the actual recorded price of each house?

  1. Feature
  2. Hyperparameter
  3. Label Correct answer.
  4. Algorithm

Explanation

The label is the target value the model is trained to predict, such as the recorded price. Features are the input columns used to make the prediction. Hyperparameters and algorithms are configuration choices, not data values.

Question 41Describe fundamental principles of machine learning on Azure

Which machine learning approach groups customers into segments without using any predefined categories?

  1. Classification
  2. Forecasting
  3. Regression
  4. Clustering Correct answer.

Explanation

Clustering is an unsupervised technique that groups records by similarity without predefined categories. Classification requires known classes, and regression predicts numeric values.

Question 42Describe fundamental principles of machine learning on Azure

A model is required to predict tomorrow's temperature in degrees Celsius. Which type of machine learning task is this?

  1. Regression Correct answer.
  2. Clustering
  3. Classification
  4. Anomaly detection

Explanation

Regression tasks predict a continuous numeric quantity such as a temperature. Classification predicts a category, and clustering discovers groups without labels.

Question 43Describe fundamental principles of machine learning on Azure

What is the primary purpose of the designer in Azure Machine Learning?

  1. To host trained models as web services for real-time scoring
  2. To monitor the cost of compute resources used by experiments
  3. To build pipelines visually by connecting modules Correct answer.
  4. To generate labeled training data automatically from raw images

Explanation

The designer is a visual authoring surface where modules representing data and model steps are connected into a pipeline. Hosting models and monitoring costs are separate capabilities of the workspace.

Question 44Describe fundamental principles of machine learning on Azure

What does automated machine learning (AutoML) in Azure Machine Learning do?

  1. It converts every trained model into a REST endpoint automatically
  2. It labels images and text using pretrained foundation models
  3. It rewrites notebooks so they run on graphics processing units
  4. It tries many algorithms and settings to find a good model Correct answer.

Explanation

Automated machine learning runs many combinations of algorithms, preprocessing steps, and hyperparameter settings, then ranks the resulting models by a chosen metric. It does not label data or convert models into endpoints.

Question 45Describe fundamental principles of machine learning on Azure

What is the purpose of training data in the machine learning process?

  1. To teach the model the relationship between features and labels Correct answer.
  2. To tune the number of layers in a deep neural network
  3. To evaluate the model after it has been deployed to production
  4. To store the version history of the model in a registry

Explanation

Training data provides the examples, including features and labels, from which the model learns patterns. Evaluation and versioning happen around training rather than through the training data itself.

Question 46Describe fundamental principles of machine learning on Azure

Why is a separate test dataset used when evaluating a model?

  1. It estimates how the model performs on data it has never seen Correct answer.
  2. It automatically balances the classes in the training data
  3. It provides additional labeled examples for the training step
  4. It reduces the amount of compute needed to train the model

Explanation

A test set is held out from training so the evaluation measures generalization to data the model has not seen. Reusing training data for evaluation would overstate performance.

Question 47Describe fundamental principles of machine learning on Azure

A classification model scores 99 percent on training data but only 62 percent on new data. What does this indicate?

  1. The model has too few features to learn
  2. The model was trained on too much data
  3. The model is overfitting the training data Correct answer.
  4. The model is underfitting the training data

Explanation

A large gap between training and holdout performance is the signature of overfitting, where the model memorizes training-specific noise. Underfitting would instead show poor results on both sets.

Question 48Describe fundamental principles of machine learning on Azure

A binary classification model has an accuracy of 0.85. What does this mean?

  1. 85 percent of predicted positives are actually positive
  2. 85 percent of the features are useful for prediction
  3. 85 percent of actual positives were correctly identified
  4. 85 percent of all predictions match the true labels Correct answer.

Explanation

Accuracy is the ratio of correct predictions to all predictions. Recall and precision describe performance on the positive class only.

Question 49Describe fundamental principles of machine learning on Azure

Which metric reports the proportion of actual positive cases that the model correctly identified?

  1. Accuracy
  2. Recall Correct answer.
  3. Specificity
  4. Precision

Explanation

Recall, also called the true positive rate, is true positives divided by all actual positives. Precision instead uses the number of positive predictions as its denominator.

Question 50Describe fundamental principles of machine learning on Azure

Which metric reports the proportion of positive predictions that were actually correct?

  1. Precision Correct answer.
  2. Recall
  3. Accuracy
  4. AUC

Explanation

Precision is true positives divided by all predicted positives, so it measures how trustworthy a positive prediction is. Recall measures coverage of actual positives.