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Microsoft AI-900 certification exam is designed to test your foundational knowledge of AI and machine learning concepts. AI-900 exam is ideal for professionals who are looking to explore the possibilities of AI and machine learning technology to drive business growth and innovation. Microsoft Azure AI Fundamentals certification exam is a great way to validate your skills and knowledge in this rapidly evolving field.
The Microsoft AI-900 exam is suitable for individuals who want to start a career in AI or individuals who want to expand their knowledge on AI and its implementation on Azure. AI-900 exam is also suitable for IT professionals who want to gain an understanding of AI and its potential applications in their organization. AI-900 Exam is an excellent opportunity for those who want to showcase their skills and expertise in AI and Azure.
Microsoft AI-900 (Microsoft Azure AI Fundamentals) certification exam is designed to provide a foundational understanding of artificial intelligence and its applications in the Azure platform. AI-900 exam is suitable for individuals who are new to AI and want to gain knowledge of its basic concepts and how it can be leveraged in the cloud. By earning this certification, candidates will demonstrate their ability to identify common AI workloads and the tools available in Azure to build intelligent solutions.
Exam AI-900 Voucher | AI-900 Valid DumpIf you purchase our study materials to prepare the AI-900 Exam, your passing rate will be much higher than others. Also, the operation of our study material is smooth and flexible and the system is stable and powerful. You can install the AI-900 exam guide on your computers, mobile phone and other electronic devices. There are no restrictions to the number equipment you install. In short, it depends on your own choice. We sincerely hope that you can enjoy the good service of our products. Microsoft Azure AI Fundamentals Sample Questions (Q31-Q36):NEW QUESTION # 31
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 # 32
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 ... -analytics/overview
NEW QUESTION # 33
You need to predict the sea level in meters for the next 10 years.
Which type of machine learning should you use?
A. regression
B. clustering
C. classification
Answer: A
Explanation:
Explanation
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Reference: https://docs.microsoft.com/en-us ... e/linear-regression
NEW QUESTION # 34
Select the answer that correctly completes the sentence Answer:
Explanation:
NEW QUESTION # 35
Your website has a chatbot to assist customers.
You need to detect when a customer is upset based on what the customer types in the chatbot.
Which type of AI workload should you use?
A. regression
B. anomaly detection
C. semantic segmentation
D. natural language processing
Answer: D
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) curriculum and Microsoft Learn module
"Explore natural language processing", NLP enables computers to understand, interpret, and analyze human language. One of its key capabilities is sentiment analysis, which detects emotional tone (positive, negative, or neutral) in text.
In this scenario, the chatbot must detect when a customer is upset based on what they type. This directly maps to sentiment analysis, a core NLP function. The Text Analytics service within Azure Cognitive Services provides prebuilt sentiment analysis models that return a sentiment score and classification (e.g., positive, neutral, negative). As per Microsoft Learn, "Natural language processing allows systems to understand sentiment and intent within text and speech to derive meaningful insights." Explanation of other options:
* A. Anomaly detection identifies unusual patterns in data (e.g., fraud detection), not emotions in text.
* B. Semantic segmentation is a computer vision technique used to label pixels in an image.
* C. Regression predicts continuous numeric values and is not related to understanding text or emotions.
Therefore, to enable the chatbot to detect when a user is upset based on text input, the correct AI workload is Natural Language Processing (NLP), specifically through Azure Text Analytics sentiment analysis.
NEW QUESTION # 36
......
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