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Exam Overview

This certification test is available in English, Spanish, Simplified Chinese, Japanese, French, Korean, and German. You will find different formats of questions while dealing with this Microsoft exam. These include multiple choice, drag and drop, build list, active screen, short answer, and best answer. The test costs $99 and the learners can register for it through Pearson VUE or Certiport.

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

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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:

  • 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.

Exam Details

The Microsoft AI-900 exam is the only qualifying test that leads to the Microsoft Certified: Azure AI Fundamentals certification. It measures one’s knowledge of AI considerations & workloads, features of NLP workloads on Azure, and basic principles of ML on Azure. The candidates can choose to take this exam in English, French, Simplified Chinese, Japanese, German, Spanish, or Korean. It contains 40-60 questions covering different types, including case studies, drag and drop, active screen, build list, and multiple choice. You can schedule your test with Certiport or Pearson VUE. However, it is required to pay the fee of $99 before scheduling it.

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Microsoft AI-900 中文 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Describe AI workloads and considerations15-20%- Identify guiding principles for responsible AI
- Identify features of common AI workloads
Topic 2: Describe features of Natural Language Processing (NLP) workloads on Azure15-20%- Describe Azure capabilities for NLP
- Identify common NLP tasks
- Identify Azure AI services for NLP
Topic 3: Describe features of Generative AI workloads on Azure15-20%- Identify responsible AI considerations for generative AI
- Describe generative AI concepts
- Describe Azure OpenAI Service capabilities
Topic 4: Describe features of computer vision workloads on Azure15-20%- Describe Azure capabilities for computer vision
- Identify common computer vision tasks
- Identify Azure AI services for computer vision
Topic 5: Describe fundamental principles of machine learning on Azure30-35%- Identify common machine learning tasks
- Describe Azure Machine Learning capabilities
- Describe features of no-code automated ML
- Describe core machine learning concepts

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