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Microsoft AI-900 Certification Exam covers a range of topics related to AI, including machine learning, natural language processing, computer vision, and cognitive services. AI-900 exam is designed to test the candidate's understanding of the core concepts of AI and how they can be applied to real-world scenarios. Candidates who pass the exam demonstrate their ability to use Microsoft Azure AI services to build intelligent solutions.
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In the last section, you will face with the following subtopics:
Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.
This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Part of the requirements for: Microsoft Certified: Azure AI Fundamentals
NEW QUESTION # 120
Match the types of natural languages processing workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Entity recognition
Classify a broad range of entities in text, such as people, places, organisations, date/time and percentages, using named entity recognition. Whereas:- Get a list of relevant phrases that best describe the subject of each record using key phrase extraction.
Box 2: Sentiment analysis
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Box 3: Translation
Using Microsoft's Translator text API
This versatile API from Microsoft can be used for the following:
Translate text from one language to another.
Transliterate text from one script to another.
Detecting language of the input text.
Find alternate translations to specific text.
Determine the sentence length.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics
NEW QUESTION # 121
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 # 122
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The correct completion of the sentence is:
"The interactive answering of questions entered by a user as part of an application is an example of natural language processing." According to the Microsoft Azure AI Fundamentals (AI-900) official study materials, Natural Language Processing (NLP) is a branch of Artificial Intelligence that focuses on enabling computers to understand, interpret, and respond to human language in a way that is both meaningful and useful. It is one of the key AI workloads described in the "Describe features of common AI workloads" module on Microsoft Learn.
When a user types a question into an application and the system responds interactively - such as in a chatbot, Q&A system, or virtual assistant - this process requires language understanding. NLP allows the system to process the input text, determine user intent, extract relevant entities, and generate an appropriate response. This is the foundational capability behind services such as Azure Cognitive Service for Language, Language Understanding (LUIS), and QnA Maker (now integrated as Question Answering in the Language service).
Microsoft's study guide explains that NLP workloads include the following key scenarios:
* Language understanding: Determining intent and context from text or speech.
* Text analytics: Extracting meaning, key phrases, sentiment, or named entities.
* Conversational AI: Powering bots and virtual agents to interact using natural language.These systems rely on NLP models to analyze user inputs and respond accordingly.
In contrast:
* Anomaly detection identifies data irregularities.
* Computer vision analyzes images or video.
* Forecasting predicts future values based on historical data.
Therefore, based on the AI-900 official materials, the interactive answering of user questions through an application clearly falls under Natural Language Processing (NLP).
NEW QUESTION # 123
You are building a Language Understanding model for an e-commerce business.
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?
Answer: C
Explanation:
Explanation
The None intent is filled with utterances that are outside of your domain.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/LUIS/luis-concept-intent
NEW QUESTION # 124
Select the answer that correctly completes the sentence
Answer:
Explanation:
NEW QUESTION # 125
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2026 Latest PrepAwayETE AI-900 PDF Dumps and AI-900 Exam Engine Free Share: https://drive.google.com/open?id=1iMdkJXTHoSo_tD2bJTBZQvcMsOzy8-ES