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Microsoft AI-900 exam is intended for individuals who do not have a technical background in AI but want to learn more about it. AI-900 exam is suitable for developers, data analysts, business analysts, and IT professionals who are interested in understanding AI concepts and how they can be implemented in Azure. Upon successful completion of the exam, candidates will be awarded the Microsoft Azure AI Fundamentals certification, which demonstrates their understanding of AI concepts and how they can be applied in a cloud computing environment.

Microsoft AI-900 (Microsoft Azure AI Fundamentals) Exam is a certification exam designed to test the fundamental knowledge of candidates in the field of artificial intelligence and machine learning. AI-900 exam is intended for individuals who want to validate their foundational knowledge of AI and its applications in the Microsoft Azure environment. AI-900 exam is suitable for technical and non-technical professionals who wish to gain knowledge and skills in AI and machine learning.

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Learning Path

All in all, Microsoft provides two ways to help candidates prepare for the Microsoft AI-900 Exam. These include the free online learning option and the paid, instructor-led training. Let’s discuss the two most popular courses offered by each of these options by the vendor:

Microsoft Azure AI Fundamentals Sample Questions (Q263-Q268):

NEW QUESTION # 263
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation


NEW QUESTION # 264
Match the types of computer vision 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 match is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 265
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:

The Azure AI Language Service includes several natural language processing features, such as question answering, language understanding, entity recognition, sentiment analysis, and more. Each feature serves a distinct purpose, and understanding their differences is key to selecting the correct AI workload.
* "You can use Azure AI Language Service's question answering to query an Azure SQL database." - NOThe question answering feature is designed to retrieve answers from text-based knowledge sources (for example, FAQs, documents, or website content). It cannot directly query a database such as Azure SQL. Querying databases requires Azure Cognitive Search, Azure OpenAI, or custom integration using application logic, not the question answering model.
* "You should use Azure AI Language Service's question answering when you want a knowledge base to provide the same answer to different users who submit similar questions." - YESThis is the primary use case of question answering. It allows developers to build a knowledge base (KB) of predefined question-answer pairs or extract answers from documents. When users submit semantically similar questions (e.g., "What are your office hours?" or "When are you open?"), the service returns the same consistent answer.
* "Azure AI Language Service's question answering can determine the intent of a user utterance." - NODetermining user intent is part of the Language Understanding (LUIS) capability, not question answering. LUIS models map natural language inputs to intents and entities, typically used in bots or applications that execute tasks (like booking a meeting or checking weather).
Hence, correct answers are: No, Yes, No - aligning with the AI-900 official study guide and Microsoft Learn module "Identify Azure AI Language capabilities."


NEW QUESTION # 266
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:

Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/qnamaker/concepts/data-sources-and-content
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service QnA maker conversational AI service and has nothing to do with SQL database You can easily create a user support bot solution on Microsoft Azure using a combination of two core technologies:
- QnA Maker. This cognitive service enables you to create and publish a knowledge base with built-in natural language processing capabilities.
- Azure Bot Service. This service provides a framework for developing, publishing, and managing bots on Azure.
https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/2-get-started-qna LUIS is used to understand user intent from utterances.
Creating a language understanding application with Language Understanding consists of two main tasks. First you must define entities, intents, and utterances with which to train the language model - referred to as authoring the model. Then you must publish the model so that client applications can use it for intent and entity prediction based on user input.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service


NEW QUESTION # 267
You have an Al solution that provides users with the ability to control smart devices by using verbal commands.
Which two types of natural language processing (NLP) workloads does the solution use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: A,E


NEW QUESTION # 268
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