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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.
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!
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Skills measured
- Implement conversational AI solutions (15-20%)
- Implement Computer Vision solutions (20-25%)
- Implement natural language processing solutions (20-25%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement knowledge mining solutions (15-20%)
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Manage security, compliance, and responsible AI - Plan solution requirements and architecture |
| Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
| Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Build Azure AI Search solutions - Enrich and index data for search scenarios |
| Implement Generative AI Solutions | - Implement Azure OpenAI Service solutions - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions |
| Implement Natural Language Processing Solutions | - Analyze text using Azure AI Language - Translate and interpret language using Azure AI services - Implement question answering and conversational AI |
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