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  • Total Questions: 336
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  • Total Questions: 336
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Target Audience

The Microsoft AI-900 exam is designed for those individuals who have little to no experience in the world of IT. It is aimed at the students with both non-technical and technical backgrounds. They have basic programming experience and knowledge. However, they are not required to have software engineering or data science experience.

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Prerequisites

This certification test has no official prerequisites. However, the interested candidates must develop their skills and knowledge in the domains of the exam topics. Although the individuals do not need this test to pursue more advanced Azure role-based options, they can gain extensive expertise while preparing for this exam. Your knowledge base can contribute to the success of more advanced certificates such as Microsoft Certified: Azure AI Engineer Associate or Microsoft Certified: Azure Data Scientist Associate.

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

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Certification Topics of Microsoft AI-900 Exam

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

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

Microsoft AI-900 Korean Exam Syllabus Topics:

SectionWeightObjectives
Describe features of computer vision workloads on Azure15-20%- Identify common computer vision tasks
- Describe Azure capabilities for computer vision
- Identify Azure AI services for computer vision
Describe features of Natural Language Processing (NLP) workloads on Azure15-20%- Identify common NLP tasks
- Describe Azure capabilities for NLP
- Identify Azure AI services for NLP
Describe AI workloads and considerations15-20%- Identify guiding principles for responsible AI
- Identify features of common AI workloads
Describe fundamental principles of machine learning on Azure30-35%- Describe core machine learning concepts
- Describe features of no-code automated ML
- Describe Azure Machine Learning capabilities
- Identify common machine learning tasks
Describe features of Generative AI workloads on Azure15-20%- Identify responsible AI considerations for generative AI
- Describe Azure OpenAI Service capabilities
- Describe generative AI concepts

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