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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.

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

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

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

  • 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.
  • 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.

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Microsoft AI-900 中文 Exam Syllabus Topics:

SectionWeightObjectives
Features of computer vision workloads on Azure15–20%- Describe capabilities of Azure Form Recognizer
- Describe capabilities of Azure Computer Vision
- Describe capabilities of Azure Custom Vision
- Describe capabilities of Azure Face
- Identify types of computer vision solutions
Fundamental principles of machine learning on Azure15–20%- Describe capabilities of Azure Machine Learning
- Describe machine learning pipelines
- Describe automated machine learning
- Describe core concepts of machine learning
Artificial Intelligence workloads and considerations15–20%- Identify types of AI workloads
- Describe considerations for developing AI solutions
- Describe responsible AI principles
Features of generative AI workloads on Azure20–25%- Describe capabilities of Azure OpenAI Service
- Describe generative AI concepts
- Describe use cases for generative AI
- Describe responsible AI practices for generative AI
Features of Natural Language Processing (NLP) workloads on Azure15–20%- Identify types of NLP solutions
- Describe capabilities of Azure Language
- Describe capabilities of Azure Speech
- Describe capabilities of Azure Translator

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