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Skills measured
- Implement natural language processing solutions (20-25%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement knowledge mining solutions (15-20%)
- Implement conversational AI solutions (15-20%)
- Implement Computer Vision solutions (20-25%)
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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.
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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The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification
- AI-102 Exam provide proven knowledge to use the tools to complete the task efficiently and cost effectively than the other non-certified professionals lack in doing so.
- This certification will be judging your skills and knowledge on your understanding Designing and Implementing an Azure AI Solution concepts & Understanding of how to operate on Planning and Administering Designing and Implementing an Azure AI Solution .
- AI-102 Certifications provide opportunities to get a job easily in which they are interested in instead of wasting years and ending without getting any experience.
- This certification credential will give you edge over other counterparts. Apart from knowledge from AI-102: Designing and Implementing an Azure AI Solution Exam.
- AI-102 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
- AI-102 credential delivers higher earning potential and increased promotion opportunities because it shows a good understanding of designing and implementing an Azure AI Solution
- AI-102 certification has more useful and relevant networks that help them in setting career goals for themselves. AI-102 networks provide them with the correct career guidance than non certified generally are unable to get.
- AI-102 Certification is distinguished among competitors. AI-102 certification can give them an edge at that time easily when candidates appear for employment interview, employers are very fascinated to note one thing that differentiates the individual from all other candidates.
- AI-102 Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Topic 2: Plan and Manage an Azure AI Solution | 15-20% | - Implement governance and compliance for AI solutions - Select appropriate Azure AI services and technologies - Plan and configure secure AI solutions - Manage AI costs and resource allocation |
| Topic 3: Implement Computer Vision Solutions | 15-20% | - Implement object detection and image classification - Analyze images using Azure AI Vision - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service - Process video and generate insights |
| Topic 4: Implement Natural Language Processing Solutions | 20-25% | - Analyze text using Azure AI Language - Translate text and speech - Build question answering solutions - Implement speech capabilities using Azure AI Speech - Create conversational AI solutions with Azure AI Bot Service |
| Topic 5: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Create custom skills for Azure AI Search - Design document processing pipelines - Implement Azure AI Search solutions - Implement semantic and vector search |
| Topic 6: Implement Generative AI Solutions | 10-15% | - Integrate Azure OpenAI models into applications - Apply responsible AI practices - Use Azure OpenAI Service for generative AI - Implement prompt engineering techniques |
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