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Microsoft AI-900 Dumps

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Microsoft Azure AI Fundamentals
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Microsoft Azure AI Fundamentals

The Microsoft Azure AI Fundamentals is an exam that tests a candidate's knowledge regarding the fundamental and foundational skills of Microsoft. These skills are as simple as the fundamentals of Machine Learning (ML), Artificial Intelligence (AI), and the concepts and skills related to the Microsoft Azure Services. The candidates who can pass the Microsoft Azure AI Fundamentals will earn the Microsoft Azure AI Fundamentals certification. By acquiring this certification, the candidate gets a chance to demonstrate their knowledge of essential ML and AI workloads. They will also be able to showcase the implementation of these workloads on Azure. The Microsoft Azure AI Fundamentals certification is meant for candidates from both technical and non-technical backgrounds. No prior data science or software engineering experience is needed, but some basic programming knowledge would help.

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The AI-900 certification, also known as the Microsoft Azure AI Fundamentals certification, validates foundational knowledge of artificial intelligence concepts and Microsoft Azure AI services. It's a great entry point for those looking to understand AI's basics and its application within the Azure cloud ecosystem.

The AI-900 exam typically consists of 45 questions. This certification assessment evaluates candidates' fundamental knowledge of artificial intelligence concepts and their ability to apply these principles within the Microsoft Azure environment.

A practical use case for classification in the AI-900 context is sentiment analysis for customer reviews. By categorizing feedback as positive, negative, or neutral, businesses can gauge customer satisfaction and make data-driven improvements to their products and services.

Microsoft AI-900 certification validates foundational knowledge in AI concepts and technologies, enhancing credibility and competence in AI-related roles. It enables professionals to effectively leverage Microsoft AI tools and solutions, driving innovation, efficiency, and success in AI projects and initiatives.

Yes, individuals with non-technical backgrounds can pursue Microsoft AI-900 certification for career advancement. The certification provides a foundational understanding of AI concepts accessible to all, allowing individuals from diverse backgrounds to explore opportunities in AI-related roles and industries.

Microsoft AI-900 certification focuses specifically on foundational knowledge and understanding of artificial intelligence (AI) concepts, principles, and applications, distinguishing it from other Microsoft exams that may cover broader topics such as cloud computing, productivity, or specific product suites.

The passing score for the Microsoft AI-900 exam is typically not publicly disclosed. It is determined through statistical analysis of exam questions and candidate performance, ensuring a fair and consistent evaluation of proficiency in AI concepts.

Microsoft updates the content of the AI-900 exam periodically to align with advancements in AI technologies and practices. These updates ensure that the exam remains relevant and reflects the latest trends, tools, and techniques in the rapidly evolving field of artificial intelligence.

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Microsoft Azure AI Fundamentals Questions and Answers

Questions 1

In which scenario should you use key phrase extraction?



translating a set of documents from English to German


generating captions for a video based on the audio track


identifying whether reviews of a restaurant are positive or negative


identifying which documents provide information about the same topics

Questions 2

You are developing a solution that uses the Text Analytics service.

You need to identify the main talking points in a collection of documents.

Which type of natural language processing should you use?



entity recognition


key phrase extraction


sentiment analysis


language detection

Questions 3

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?



entity recognition


key phrase extraction


sentiment analysis