Microsoft : AI-900 Korean Questions & Answers

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Certification Path

The Azure AI Fundamentals certification might not be a prerequisite for any other certification levels, however, it can still be used to prepare for multiple Azure-related qualifications including the Microsoft Certified: Azure Data Scientist Associate and the Microsoft Certified: Azure AI Engineer Associate.

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Explain Conversational Artificial Intelligence Workloads Features on Azure (15-20%)

In the last section, you will face with the following subtopics:

• Identify the basic use cases for Conversational Artificial Intelligence (AI) – The students should be able to identify the features and usage for a range of elements. These include personal digital assistants, webchat bots, and telephone voice menus. It also covers the skills in identifying the basic features of conversational Artificial Intelligence solutions.
• Establish Azure services for Conversational Artificial Intelligence – The potential candidates for the Microsoft AI-900 exam should have the capacity to identify the capabilities of Azure Bot Service and QnA Maker service.

Certification Topics of Microsoft AI-900 Exam

Our Microsoft AI-900 exam dumps covers the following objectives of Microsoft AI-900 Exam.

• Describe AI workloads and considerations (15-20%)
• Describe features of computer vision workloads on Azure (15-20%)
• Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
• Describe fundamental principles of machine learning on Azure (30-35%)
• Describe features of conversational AI workloads on Azure (15-20%)

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian

Retirement date: none

Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; features of Natural Language Processing (NLP) workloads on Azure; and features of conversational AI workloads on Azure.

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