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Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:
| Passing Score | 700 / 1000 |
| Books / Training | Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Duration | 130 mins |
| Exam Price | $165 (USD) |
| Number of Questions | 40-60 |
| Schedule Exam | Pearson VUE |
| Exam Name | Microsoft Certified - Azure AI Engineer Associate |
| Sample Questions | Designing and Implementing a Microsoft Azure AI Solution Sample Questions |
| Exam Code | AI-102 |
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The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
For more info read reference:
microsoft learning site AI-102 Skills measured Publish a Machine Learning Experiment with Microsoft Azure Machine Learning Studio Process and translate speech with Azure Cognitive Speech Services
Topics Covered
Exam AI-102 contains five topics each of which is intended to check specific skills.
1. Plan and Manage an Azure Cognitive Services Solution
This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.
2. Implement Computer Vision Solutions
The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.
3. Implement Natural Language Processing Solutions
In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.
4. Implement Knowledge Mining Solutions
In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.
5. Implement Conversational AI Solutions
This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.
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Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language |
| Topic 2: Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Manage security, compliance, and responsible AI - Select appropriate Azure AI services |
| Topic 3: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Implement custom vision models - Extract information using OCR and form recognition |
| 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 | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |








