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Passing the AI-900 Exam will demonstrate your ability to understand the basic concepts and principles of AI and its applications in the cloud. Microsoft Azure AI Fundamentals certification can help you stand out in the job market and increase your chances of getting hired for roles related to AI and machine learning. It can also help you advance your career by providing a solid foundation for further learning and certifications in this field.
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The AI-900 exam covers various AI technologies, including machine learning, natural language processing, computer vision, and cognitive services. AI-900 exam assesses candidates' knowledge of Azure AI services, including Azure Machine Learning, Azure Cognitive Services, and Azure Bot Service. AI-900 exam also evaluates candidates' understanding of AI workloads and how to create and manage AI solutions using Azure tools and services. Passing the AI-900 Exam demonstrates that candidates have foundational knowledge of AI concepts and the ability to leverage Azure AI services to build intelligent solutions.
NEW QUESTION # 297
You plan to build a conversational Al solution that can be surfaced in Microsoft Teams. Microsoft Cortana, and Amazon Alexa. Which service should you use?
Answer: B
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe features of conversational AI workloads on Azure," the Azure Bot Service is the dedicated Azure service for building, connecting, deploying, and managing conversational AI experiences across multiple channels - such as Microsoft Teams, Cortana, and Amazon Alexa.
The Azure Bot Service integrates with the Bot Framework SDK to design intelligent chatbots that can communicate with users in natural language. It also connects seamlessly with other Azure Cognitive Services, such as Language Service (LUIS) for intent understanding and Speech Service for voice input/output.
The question specifies that the conversational AI must be accessible through multiple platforms, including Microsoft Teams, Cortana, and Alexa. Azure Bot Service supports this multi-channel communication model out of the box, allowing developers to configure a single bot that interacts through many endpoints simultaneously.
Other options:
* B. Azure Cognitive Search: Used for information retrieval and knowledge mining, not conversational AI.
* C. Language Service: Provides natural language understanding, key phrase extraction, sentiment analysis, etc., but doesn't handle multi-channel communication.
* D. Speech: Provides speech-to-text and text-to-speech conversion but is not a chatbot platform.
Therefore, the best solution for building and deploying a multi-channel conversational AI system is Azure Bot Service, as clearly defined in Microsoft's AI-900 learning content.
NEW QUESTION # 298
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-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.
NEW QUESTION # 299
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
With Microsoft's Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more.
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and
NEW QUESTION # 300
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 # 301
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Text Description automatically generated
Regression is a machine learning task that is used to predict the value of the label from a set of related features.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks
NEW QUESTION # 302
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