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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Available Languages: | Chinese (Traditional), French, Chinese (Simplified), Arabic (Saudi Arabia), German, Korean, Russian, Italian, Spanish, Japanese, Portuguese (Brazil), English, Indonesian (Indonesia) |
| Exam Price: | USD 99 |
| Certificate Validity Period: | 1 year (renewable via free online assessment on Microsoft Learn) |
| Passing Score: | 700 / 1000 |
| Real Exam Qty: | 40-60 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Format: | Drag and drop, Multiple select, Match the service to use case, Scenario-based, Multiple choice |
| Exam Duration: | 45-60 |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online (remote proctored via Pearson VUE) or at a Pearson VUE test center |
| Pre Condition: | No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900 |
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NEW QUESTION # 71
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Counting the number of animals in an area based on a video feed is an example of computer vision.
Computer vision is the AI workload used to analyze visual content such as images and video. Counting animals in a video feed requires detecting visual objects in video frames and analyzing them, which is a computer vision task.
Forecasting predicts future values or trends from historical data.
Knowledge mining extracts insights from large document or data collections.
Therefore, the correct answer is computer vision.
NEW QUESTION # 72
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: Human-in-the-loop practices provide accountability for AI-generated decisions. = Yes Microsoft responsible AI guidance recommends keeping a human in the loop, maintaining human oversight, and ensuring humans have a role in decisions based on model output.
Statement 2: Deploying an AI system to a production environment eliminates the need for ongoing monitoring. = No Microsoft guidance states that after deployment, an AI-powered product or feature requires ongoing monitoring and improvement.
Statement 3: Disclosing the team that designed and deployed an AI system provides accountability for the system's output. = Yes Accountability in responsible AI means people and organizations remain responsible for AI systems and their effects. Identifying the people or team responsible for designing and deploying the system supports accountability and governance.
NEW QUESTION # 73
You need to convert written customer notifications into natural-sounding spoken audio that can be played over a phone system. Which Azure Speech in Foundry Tools capability should you use?
Answer: B
Explanation:
The requirement is to convert written customer notifications into natural-sounding spoken audio.
This is speech synthesis, also known as text to speech.
Microsoft's Azure Speech documentation describes text to speech as a capability that converts text into natural-sounding synthesized speech. Therefore, for playing written notifications over a phone system, the correct Azure Speech capability is speech synthesis.
NEW QUESTION # 74
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 75
You have a dataset that contains experimental data for fuel samples.
You need to predict the amount of energy in kilojoules that can be obtained from a sample based on its measured density.
Which type of AI workload should you use?
Answer: D
Explanation:
Regression is a supervised machine learning technique which is used to predict continuous values. The ultimate goal of the regression algorithm is to plot a best-fit line or a curve between the data. The three main metrics that are used for evaluating the trained regression model are variance, bias and error.
Reference:
https://builtin.com/data-science/regression-machine-learning
NEW QUESTION # 76
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