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Prep Options to Choose
The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.
In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!
Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution
Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Plan and Manage an Azure AI Solution | 15-20% | - Implement governance and compliance for AI solutions - Select appropriate Azure AI services and technologies - Manage AI costs and resource allocation - Plan and configure secure AI solutions |
| Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Use Azure OpenAI Service for generative AI - Implement prompt engineering techniques - Apply responsible AI practices |
| Implement Natural Language Processing Solutions | 20-25% | - Implement speech capabilities using Azure AI Speech - Build question answering solutions - Create conversational AI solutions with Azure AI Bot Service - Analyze text using Azure AI Language - Translate text and speech |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Design document processing pipelines - Implement semantic and vector search - Create custom skills for Azure AI Search |
| Implement Decision Support Solutions | 10-15% | - Integrate Azure AI services into applications - Design and implement decision automation - Monitor and optimize decision support solutions |
| Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Analyze images using Azure AI Vision - Implement object detection and image classification - Implement Azure AI Face service - Read and process documents using Azure AI Document Intelligence |
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