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Microsoft AI-102 valid - in .pdf

AI-102 pdf
  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution
  • Q & A: 425 Questions and Answers
  • PDF Price: $59.99
  • Free Demo

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  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution
  • Q & A: 425 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft AI-102 valid - Testing Engine

AI-102 Testing Engine
  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution
  • Q & A: 425 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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AI-102: Designing and Implementing an Azure AI Solution Exam Certified Professional salary

The average salary of a AI-102: Designing and Implementing an Azure AI Solution Exam Certified Expert in

  • India - 20,00,327 INR
  • Europe - 90,547 EURO
  • United State - 120,000 USD
  • England - 90,532 POUND

What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam

  • This is beta exam.
  • Type of Questions: This test format is multiple choice.
  • Language: English, Japanese, Chinese (Simplified), Korean.
  • Passing Score: 700 / 1000
  • Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • Length of Examination: 50 mins

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

Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Implement an agentic solution5-10%- Test, deploy, and optimize agents
- Develop multi-agent workflows and orchestration
- Build agents with Microsoft Foundry Agent Service
- Understand agent use cases and types
Implement computer vision solutions10-15%- Integrate vision capabilities into applications
- Process and index video content
- Extract text and handwriting from images
- Analyze images and detect objects/features
- Build and deploy custom vision models
Implement natural language processing solutions15-20%- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
- Build conversational AI and chatbots
- Implement translation and summarization
Implement knowledge mining and information extraction solutions15-20%- Ingest and process structured/unstructured data
- Build knowledge bases and search indexes
- Extract entities, relationships, and key phrases
- Implement intelligent search and retrieval
Implement generative AI solutions15-20%- Orchestrate multiple models and containers
- Implement model monitoring and feedback
- Apply prompt engineering and fine-tuning
- Integrate Azure OpenAI and other generative models
- Deploy and manage generative models
Plan and manage an Azure AI solution20-25%- Plan solutions aligned with responsible AI principles
- Select suitable AI models
- Monitor, optimize, and secure AI solutions
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Create and configure Azure AI resources
- Select appropriate Microsoft Foundry Services

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