AI Workloads & Machine Learning — AI-900 Practice Question
A representative Microsoft Azure AI Fundamentals (AI-900) exam question on AI Workloads & Machine Learning. Work through it below, then read why each option is right or wrong.
Short answer
The correct answer is C. Predictive Analytics.
Predictive Analytics is the correct answer because it involves using historical data to make predictions about future outcomes. Forecasting inventory needs based on past sales data is a classic predictive analytics use case. Computer Vision (A) processes images and video. Natural Language Processing (B) works with text and speech. Knowledge Mining (D) extracts insights from unstructured content like documents.
The Question
A retail company wants to use historical sales data to forecast inventory needs for the next quarter. Which type of AI workload best describes this scenario?
Why C is correct
Predictive Analytics is the correct answer because it involves using historical data to make predictions about future outcomes. Forecasting inventory needs based on past sales data is a classic predictive analytics use case. Computer Vision (A) processes images and video. Natural Language Processing (B) works with text and speech. Knowledge Mining (D) extracts insights from unstructured content like documents.
Why the other options are wrong
Option A does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (C) is the only one that fully meets every constraint stated in the question.
Option B does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (C) is the only one that fully meets every constraint stated in the question.
Option D does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (C) is the only one that fully meets every constraint stated in the question.
Key idea: AI Workloads & Machine Learning
Predictive Analytics is the correct answer because it involves using historical data to make predictions about future outcomes. Forecasting inventory needs based on past sales data is a classic predictive analytics use case. Computer Vision (A) processes images and video. Natural Language Processing (B) works with text and speech. Knowledge Mining (D) extracts insights from unstructured content like documents. On the AI-900 exam, questions in the "AI Workloads and Considerations" domain test whether you can map a scenario's constraints to the right choice. Read the requirement carefully, eliminate options that violate any single constraint, and pick the one that satisfies all of them with the least operational overhead.
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