Mar-2026 Microsoft AI-900 Actual Questions and 100% Cover Real Exam Questions
AI-900 Free Exam Questions and Answers PDF Updated on Mar-2026
What is the duration, language, and format of AI-900: Microsoft Azure AI Fundamentals Exam
- Length of Examination: 50 mins
- Languages in which this exam is available in: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish
- Type of Questions: This test format is multiple choice
- Number of Questions: 100 to 120 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice)
- Passing Score: 70%
NEW QUESTION # 43
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 44
Which AI service can you use to interpret the meaning of a user input such as "Call me back later?"
- A. Translator Text
- B. Text Analytics
- C. Language Understanding (LUIS)
- D. Speech
Answer: C
Explanation:
Explanation
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis
NEW QUESTION # 45
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:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview
NEW QUESTION # 46
You need to predict the income range of a given customer by using the following dataset.
Which two fields should you use as features? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Last Name
- B. Education Level
- C. First Name
- D. Income Range
- E. Age
Answer: B,E
Explanation:
First Name, Last Name, Age and Education Level are features. Income range is a label (what you want to predict). First Name and Last Name are irrelevant in that they have no bearing on income. Age and Education level are the features you should use.
NEW QUESTION # 47
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:
NEW QUESTION # 48
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:
Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/text-analytics/overview
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-services/ You can use the Speech service to transcribe a call to text - Yes we can use Speech to Text API to achieve this
https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction You can use a speech service to translate the audio of a call to a different language - Yes we can use Speech translation service to achieve this The Speech service includes the following application programming interfaces (APIs):
Speech-to-text - used to transcribe speech from an audio source to text format.
Text-to-speech - used to generate spoken audio from a text source.
Speech Translation - used to translate speech in one language to text or speech in another.
https://docs.microsoft.com/en-us/learn/modules/translate-text-with-translation-service/2-get-started-azure You can use text analytics service to extract key entities from a call transcript -Yes Text Analytics API helps to achieve this
https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure
NEW QUESTION # 49
You plan to deploy an Azure Machine Learning model by using the Machine Learning designer Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
1 - Ingest and prepare a dataset.
2 - Split the data randomly into training data and validation data
3 - Train the model.
4 - Evaluation the model against the validation dataset.
NEW QUESTION # 50
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
- A. classification
- B. regression
- C. clustering
Answer: C
Explanation:
Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks
NEW QUESTION # 51
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
NEW QUESTION # 52
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.
Answer:
Explanation:
1 - data prparation
2 - model training
3 - model evaluation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines
NEW QUESTION # 53
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:
Yes, No, Yes.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify capabilities of Azure Cognitive Services for Language", the Azure Translator service is a cloud-based machine translation service used to translate text or entire documents between languages in real time. It uses REST APIs or client libraries to translate text input, detect languages, and support multiple target languages in a single request.
* "The following service call will accept English text as an input and output Italian and French text:
/translate?from=en&to=it,fr - Yes.This URL format is correct because the Translator service API allows multiple target languages to be specified in a single to parameter separated by commas. In this case, from=en defines the source language (English), and to=it,fr requests translations into Italian (it) and French (fr). The API would return results in both target languages simultaneously. This syntax is officially documented in Microsoft Learn as the valid format for multi-language translation.
* "The following service call will accept English text as an input and output Italian and French text:
/translate?from=en&to=fr&to=it - No.This format is incorrect, as the Translator API does not support repeating the to parameter multiple times. Only one to parameter is valid, and multiple target languages must be provided as a comma-separated list within the same to parameter.
* "The Translator service can be used to translate documents from English to French." - Yes.This statement is true. The Translator service supports both text translation and document translation. The document translation capability allows the translation of whole files such as Word, PowerPoint, or PDF documents while preserving formatting and structure. This feature is included in the official Translator API under "Document Translation." In summary, the AI-900 study content clarifies that:
# /translate?from=en&to=it,fr # Valid syntax
# /translate?from=en&to=fr&to=it # Invalid syntax
# Translator can translate full documents between languages
NEW QUESTION # 54
You need to use Azure Machine Learning designer to build a model that will predict automobile prices.
Which type of modules should you use to complete the model? To answer, drag the appropriate modules to the correct locations. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-train-score
NEW QUESTION # 55
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Text Description automatically generated
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-label-data
NEW QUESTION # 56
You use natural language processing to process text from a Microsoft news story.
You receive the output shown in the following exhibit.
Which type of natural languages processing was performed?
- A. key phrase extraction
- B. sentiment analysis
- C. translation
- D. entity recognition
Answer: D
Explanation:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview
NEW QUESTION # 57
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:
NEW QUESTION # 58
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
Reliability & Safety
https://en.wikipedia.org/wiki/Tay_(bot)
"To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation. It's also important to be able to verify that these systems are behaving as intended under actual operating conditions. How they behave and the variety of conditions they can handle reliably and safely largely reflects the range of situations and circumstances that developers anticipate during design and testing. We believe that rigorous testing is essential during system development and deployment to ensure AI systems can respond safely in unanticipated situations and edge cases, don't have unexpected performance failures, and don't evolve in ways that are inconsistent with original expectations"
NEW QUESTION # 59
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 60
You are developing a solution that uses the Text Analytics service.
You need to identify the main talking points in a collection of documents.
Which type of natural language processing should you use?
- A. sentiment analysis
- B. key phrase extraction
- C. entity recognition
- D. language detection
Answer: B
Explanation:
Explanation
Broad entity extraction: Identify important concepts in text, including key Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
NEW QUESTION # 61
Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml
NEW QUESTION # 62
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
Graphical user interface, text, application Description automatically generated
NEW QUESTION # 63
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