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Microsoft AI-900 Exam Syllabus Topics:

SectionWeightObjectives
Describe features of Natural Language Processing (NLP) workloads on Azure15-20%- Identify Azure AI services for NLP
- Identify common NLP tasks
- Describe Azure capabilities for NLP
Describe AI workloads and considerations15-20%- Identify features of common AI workloads
- Identify guiding principles for responsible AI
Describe features of Generative AI workloads on Azure15-20%- Identify responsible AI considerations for generative AI
- Describe generative AI concepts
- Describe Azure OpenAI Service capabilities
Describe fundamental principles of machine learning on Azure30-35%- Describe core machine learning concepts
- Describe Azure Machine Learning capabilities
- Identify common machine learning tasks
- Describe features of no-code automated ML
Describe features of computer vision workloads on Azure15-20%- Describe Azure capabilities for computer vision
- Identify Azure AI services for computer vision
- Identify common computer vision tasks

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Microsoft Azure AI Fundamentals Sample Questions (Q271-Q276):

NEW QUESTION # 271
You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?

Answer: A

Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation:
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language- processing


NEW QUESTION # 272
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?

Answer: B

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 # 273
Select the answer that correctly completes the sentence

Answer:

Explanation:

Explanation:


NEW QUESTION # 274
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?

Answer: B

Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation:
Named Entity Recognition (NER) is the ability to identify different entities in text and categorize them into pre- defined classes or types such as: person, location, event, product, and organization.
In this question, the square brackets indicate the entities such as DateTime, PersonType, Skill.
Reference:
https://docs.microsoft.com/en-in/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity- linking?tabs=version-3-preview


NEW QUESTION # 275
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:

According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of Computer Vision workloads on Azure", the Custom Vision service is a part of Azure Cognitive Services that allows users to build, train, and deploy custom image classification and object detection models. It is primarily designed for still-image analysis, not video processing.
* "The Custom Vision service can be used to detect objects in an image." - Yes.This is correct. The Custom Vision service supports two major model types: classification (categorizing entire images) and object detection (identifying and locating multiple objects within a single image). In object detection mode, the model outputs both the object's category and its position in the image using bounding boxes.
This capability is emphasized in the AI-900 curriculum as an example of applying computer vision to real-world scenarios, such as identifying products on shelves or detecting equipment parts in manufacturing.
* "The Custom Vision service requires that you provide your own data to train the model." - Yes.This statement is also true. Unlike prebuilt computer vision models, Custom Vision is a trainable model that requires users to upload their own labeled images to create a domain-specific AI model. The model's accuracy depends on the quality and quantity of this user-provided data. The AI-900 study materials explain that Custom Vision is used when prebuilt models do not meet specific needs, enabling businesses to train models tailored to unique image sets.
* "The Custom Vision service can be used to analyze video files." - No.This is incorrect. Custom Vision is limited to image-based analysis. To analyze video content (detecting objects or motion in moving frames), Azure provides Video Indexer, which is a separate service designed for extracting insights from video files, including speech, objects, faces, and emotions.


NEW QUESTION # 276
......

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