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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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AI-102: Designing and Implementing an Azure AI Solution Certification Path

The Microsoft Designing and Implementing an Azure AI Solution Certification includes only one AI-100 Exam.

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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

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How to Prepare For AI-102: Designing and Implementing an Azure AI Solution Exam

Preparation Guide for AI-102: Designing and Implementing an Azure AI Solution Exam

Introduction

Microsoft has created a track for Azure professionals analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements, to get certified this platform. solution architects translate the vision and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets Microsoft's proficiency standards.

This certification been actually designed for aspirants design and implement AI apps and agents that use Microsoft Azure Cognitive Services.

For this exam candidate having proficiency in using cognitive service APIs to meet business requirements, appropriate AI models and services, automation requirements, data privacy and protection , bot state data , cognitive service output would be an added advantage.

Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work as AI solution architect and prove his knowledge, certification offered by Microsoft. This AI-102 Exam Certification helps a candidate to validates his skills in Azure platform.

In this guide, we will cover the AI-102: Designing and Implementing an Azure AI Solution Certification exam, AI-102: Designing and Implementing an Azure AI Solution Certified professional salary and all aspects of the AI-102: Designing and Implementing an Azure AI Solution Certification.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Implement Knowledge Mining and Document Intelligence Solutions15-20%- Create custom skills for Azure AI Search
- Implement Azure AI Search solutions
- Design document processing pipelines
- Implement semantic and vector search
Plan and Manage an Azure AI Solution15-20%- Select appropriate Azure AI services and technologies
- Plan and configure secure AI solutions
- Implement governance and compliance for AI solutions
- Manage AI costs and resource allocation
Implement Generative AI Solutions10-15%- Use Azure OpenAI Service for generative AI
- Implement prompt engineering techniques
- Integrate Azure OpenAI models into applications
- Apply responsible AI practices
Implement Computer Vision Solutions15-20%- Analyze images using Azure AI Vision
- Read and process documents using Azure AI Document Intelligence
- Implement object detection and image classification
- Process video and generate insights
- Implement Azure AI Face service
Implement Natural Language Processing Solutions20-25%- Translate text and speech
- Build question answering solutions
- Implement speech capabilities using Azure AI Speech
- Analyze text using Azure AI Language
- Create conversational AI solutions with Azure AI Bot Service
Implement Decision Support Solutions10-15%- Monitor and optimize decision support solutions
- Integrate Azure AI services into applications
- Design and implement decision automation

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