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For candidates that are aiming to develop their skills in building, operating, and deploying AI solutions with the help of such services as Azure Applied AI services and Azure Cognitive Services, the best variant is to pass the Microsoft AI-102 exam. This exam is all about designing and applying a Microsoft Azure AI Solution, and leads to getting the Microsoft Certified: Azure AI Engineer Associate certification.
Passing this exam implies that certified candidates are able to participate in all stages of AI solutions development from defining requirements to performance tuning and monitoring. These professionals cooperate with solution architects, as well as with data engineers and scientists, AI developers to show their vision and create comprehensive AI solutions.
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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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | 15-20% | - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions |
| Topic 2: Implement Generative AI Solutions | 10-15% | - Implement prompt engineering techniques - Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Integrate Azure OpenAI models into applications |
| Topic 3: Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Integrate Azure AI services into applications - Design and implement decision automation |
| Topic 4: Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Build question answering solutions - Implement speech capabilities using Azure AI Speech - Translate text and speech - Create conversational AI solutions with Azure AI Bot Service |
| Topic 5: Implement Computer Vision Solutions | 15-20% | - Analyze images using Azure AI Vision - Implement object detection and image classification - Process video and generate insights - Implement Azure AI Face service - Read and process documents using Azure AI Document Intelligence |
| Topic 6: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Create custom skills for Azure AI Search - Design document processing pipelines - Implement semantic and vector search |
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