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Main Prerequisites
Before you decide to take the Microsoft AI-100 exam, it is important that you understand all the knowledge requirements for this test. The exam is not designed for the general public, so you need to possess certain competence before attempting it. The target candidates for this certification test should have the following skills:
- Familiarity with data storage in Azure, Azure Cognitive Search, Microsoft Azure Cognitive Services, and Azure Bot Service.
- Understanding when a custom API should be developed to satisfy certain business requirements.
- Ability to put forward solutions that utilize open source technologies with understanding the elements that make up the Azure AI portfolio along with the available data storage options.
- Expertise in implementing and designing AI applications and agents that utilize Microsoft Azure Cognitive Services.
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Preparation Process
If you are planning to take the Microsoft AI-100 exam, it is very important that you prepare for it thoroughly. It doesn’t matter if you have a lot of experience in the field because if you don’t study for this certification test, there is a big chance that you will not be able to pass it. To prepare for the AI-100 exam, the first thing that every candidate needs to do is visit the official website. Here you will find a plethora of reliable resources that will convey all the authentic information to you. On this online platform, you will also find a few free learning paths that will allow you to understand all the details of your Microsoft test. These paths are as follows:
- Processing and Classifying Images with Azure Cognitive Vision Services
- Processing and Translating Speech with Azure Cognitive Speech Services
- Evaluating Text with Azure Cognitive Language Services
- Creating Intelligent Bots with the Azure Bot Service
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Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx
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Microsoft AI-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement and Monitor AI Solutions | 25-30% | - Configure security and access controls - Monitor performance, usage, and health - Integrate AI models and services into applications - Maintain and update AI solutions - Deploy AI solutions to Azure infrastructure |
| Design AI Solutions | 40-45% | - Design computer vision solutions - Integrate open-source and custom AI components - Design knowledge mining and search solutions - Select appropriate Azure Cognitive Services - Design natural language processing solutions - Design conversational AI and bot solutions |
| Analyze Solution Requirements | 25-30% | - Evaluate data storage and processing options - Define solution performance and scalability criteria - Identify business and technical requirements - Assess security, compliance, and governance needs |








