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

Exam Topics

The potential candidates for this certification test must develop their skills in its topics before attempting it. It is recommended to go through the official webpage to review the detailed objectives. Microsoft updates the topics of its exams regularly, so studying the latest domains is very important to your success in the test. Thus, Microsoft AI-900 covers the following sections:

Describe AI Considerations and Workloads (15-20%)

The first topic evaluates the following skills:

  • Identify the common AI Workloads features – You should be able to identify a variety of workloads, such as forecasting/prediction, computer vision, and conversational AI. The subsection also covers the characteristics of anomaly detection workloads, knowledge mining, and natural language processing workloads.
  • Identify the guiding principles associated with responsible Artificial Intelligence – This one will evaluate the candidates’ ability to explain some concepts. These include considerations of safety and reliability in AI solutions and considerations for fairness in AI solutions. It also covers considerations for security and privacy, transparency, inclusiveness, and accountability within an AI solution.

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Microsoft AI-900 中文 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Features of computer vision workloads on Azure15–20%- Identify types of computer vision solutions
- Describe capabilities of Azure Face
- Describe capabilities of Azure Custom Vision
- Describe capabilities of Azure Computer Vision
- Describe capabilities of Azure Form Recognizer
Topic 2: Features of Natural Language Processing (NLP) workloads on Azure15–20%- Describe capabilities of Azure Speech
- Describe capabilities of Azure Language
- Identify types of NLP solutions
- Describe capabilities of Azure Translator
Topic 3: Features of generative AI workloads on Azure20–25%- Describe responsible AI practices for generative AI
- Describe capabilities of Azure OpenAI Service
- Describe generative AI concepts
- Describe use cases for generative AI
Topic 4: Artificial Intelligence workloads and considerations15–20%- Describe considerations for developing AI solutions
- Identify types of AI workloads
- Describe responsible AI principles
Topic 5: Fundamental principles of machine learning on Azure15–20%- Describe machine learning pipelines
- Describe capabilities of Azure Machine Learning
- Describe automated machine learning
- Describe core concepts of machine learning

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