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Requisites of Microsoft AI-900 Exam

In order to take the Microsoft AI-900 exam, you must have a current Azure subscription. You also need a valid Microsoft ID. In addition, be sure to pass the following exams:

  • AZ-100: Fundamentals of Azure
  • AZ-200: Azure Fundamentals Assessment

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

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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.

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Describe the Basic Principles of ML on Microsoft Azure (30-35%)

As for this area, it includes the following:

  • Describe the ML core concepts – You should be able to identify the labels and features within a dataset for ML and describe the usage of validation datasets and training in ML. The applicants also need the ability to explain the usage of ML algorithms in model training, as well as interpret and choose the model evaluation yardsticks for regression and classification.
  • Identify the basic ML types – This section equips the learners with the ability to identify various concepts, such as regression, clustering, and classification ML scenarios.
  • Identify the major tasks in crafting an ML solution – This subject area measures the students’ competence in explaining some concepts, such as basic features of data preparation and ingestion, model management and deployment, model training & evaluation, and feature selection and engineering.
  • Explain the abilities of the No-code ML with Azure ML Learning Studio – This domain equips the individuals with the knowledge of the Azure ML designer and automated ML UI.

Microsoft AI-900日本語 Exam Syllabus Topics:

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

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