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What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam
- Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
- Length of Examination: 50 mins
- Passing Score: 700 / 1000
- This is beta exam.
- Language: English, Japanese, Chinese (Simplified), Korean.
- Type of Questions: This test format is multiple choice.
Schedule exam
Languages: English, Japanese, Chinese (Simplified), Korean
Retirement date: none
This exam measures your ability to accomplish the following technical tasks: plan and manage an Azure Cognitive Services solutions; implement Computer Vision solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions.
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Prerequisites
Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Implement Computer Vision Solutions | - Implement custom vision models - Analyze images and videos using Azure AI Vision - Extract information using OCR and form recognition |
| Topic 2: Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Plan solution requirements and architecture - Manage security, compliance, and responsible AI |
| Topic 3: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Implement question answering and conversational AI - Analyze text using Azure AI Language |
| Topic 4: Implement Generative AI Solutions | - Build retrieval-augmented generation (RAG) solutions - Implement Azure OpenAI Service solutions - Integrate prompt engineering techniques |
| Topic 5: Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Implement document intelligence solutions - Build Azure AI Search solutions |
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