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AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure

Match each Azure AI concept to its definition.

Drag a concept onto its matching description — or click a concept then click the description.

Concepts
Matches

Probability that a prediction is correct

Coordinates around an object in an image

Identify main topics in text

Determine positive, negative, or neutral tone

Identify named entities like people or places

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Anomaly Detector: Identifies unusual patterns or outliers in data.

The correct matches are: Anomaly Detector detects unusual patterns, Computer Vision analyzes visual data, NLP processes human language, and Speech Services handles audio conversion. The distractors swap definitions between Anomaly Detector and Computer Vision.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Anomaly Detector: Identifies unusual patterns or outliers in data.

    Why this is correct

    Anomaly Detector is a dedicated Azure AI service that applies statistical and machine learning models to time-series and batch data to automatically identify unusual patterns, spikes, drops, or outliers. It provides pre-built algorithms for univariate and multivariate anomaly detection, enabling monitoring of metrics without requiring custom model training. This definition correctly describes the service's core purpose.

  • Computer Vision: Extracts information from images, videos, and other visual inputs.

    Why this is correct

    Computer Vision is an Azure AI service that uses pre-trained deep learning models to analyze visual content, including images, videos, and other visual inputs. It can extract rich information such as objects, faces, landmarks, printed or handwritten text (OCR), image tags, and even color schemes. This extraction of structured information from visual data is precisely what the definition states.

  • Natural Language Processing: Processes and analyzes human language to understand sentiment, extract key phrases, etc.

    Why this is correct

    Natural Language Processing (NLP) is a branch of Azure AI that enables applications to process and analyze human language in text form. Azure AI Language provides capabilities such as sentiment analysis, key phrase extraction, language detection, named entity recognition, and question answering by applying linguistic and machine learning models. Therefore, the definition accurately captures the essence of NLP in Azure.

  • Speech Services: Converts spoken language into text and vice versa.

    Why this is correct

    Speech Services, part of Azure AI, delivers speech-to-text (STT) and text-to-speech (TTS) conversion, along with speech translation and speaker recognition. It uses acoustic and language models to transcribe spoken language into written text and synthesize natural-sounding speech from text. Thus the definition 'Converts spoken language into text and vice versa' is a concise and accurate match.

  • Anomaly Detector: Extracts information from images, videos, and other visual inputs.

    Why it's wrong here

    Although Anomaly Detector is an Azure AI service, it does not extract information from images, videos, or visual inputs; that functionality belongs to Computer Vision. Anomaly Detector numerically analyzes time-series data to identify unusual patterns or outliers, such as sudden spikes or drops in metrics. The definition is mismatched, making this pairing incorrect.

  • Computer Vision: Identifies unusual patterns or outliers in data.

    Why it's wrong here

    While Computer Vision can identify patterns in images, it is not designed to detect outliers or unusual patterns in data; that is the role of Anomaly Detector. Computer Vision focuses on interpreting visual content—objects, faces, OCR text, and scenes—rather than statistical anomaly detection in numeric datasets. Pairing Computer Vision with this data-outlier definition is therefore incorrect.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-900 exam.