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Main Prerequisites

Before you decide to take the Microsoft AI-100 exam, it is important that you understand all the knowledge requirements for this test. The exam is not designed for the general public, so you need to possess certain competence before attempting it. The target candidates for this certification test should have the following skills:

  • Ability to put forward solutions that utilize open source technologies with understanding the elements that make up the Azure AI portfolio along with the available data storage options.
  • Understanding when a custom API should be developed to satisfy certain business requirements.
  • Familiarity with data storage in Azure, Azure Cognitive Search, Microsoft Azure Cognitive Services, and Azure Bot Service.
  • Expertise in implementing and designing AI applications and agents that utilize Microsoft Azure Cognitive Services.

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Skills measured

  • Design AI solutions (40-45%)
  • Analyze solution requirements (25-30%)
  • Implement and monitor AI solutions (25-30%)

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Exam AI-100: Designing and Implementing an Azure AI Solution

THIS EXAM RETIRED ON JUNE 30, 2021. A replacement exam, AI-102, is available. For more information, visit the AI-102 exam details page.

Candidates for this exam should have subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.

Responsibilities for an Azure AI Engineer include analyzing requirements for AI solutions, recommending the appropriate tools and technologies, and designing and implementing AI solutions that meet scalability and performance requirements.

Azure AI Engineers translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and software developers to build complete end-to-end solutions.

A candidate for this exam should have knowledge and experience designing and implementing AI apps and agents that use Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure. In addition, a candidate should be able to recommend solutions that use open source technologies, understand the components that make up the Azure AI portfolio and the available data storage options, and understand when a custom API should be developed to meet specific requirements.

Part of the requirements for: none

Download exam skills outline

Microsoft AI-100 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Integrate Intelligent Edge With Solutions
  • Design Pre-Processing And Processing Strategy For Iot Data
Topic 2
  • Design Intelligent Edge Solutions
  • Design Data Governance
  • Design Solutions That Adhere To Cost Constraints
Topic 3
  • Map Security Requirements To Tools, Technologies, And Processes
  • Determine Which Users And Groups Have Access To Information And Interfaces
Topic 4
  • Validate Solutions To Ensure Compliance With Data Privacy And Security Requirements
  • Monitor And Evaluate The AI Environment
Topic 5
  • Analyze Solution Requirements
  • Identify Storage Solutions
Topic 6
  • Deploy And Manage Solutions
  • Provision Required Cloud, On-Premises, And Hybrid Environments
Topic 7
  • Identify Appropriate Tools For A Solution
  • Identify Auditing Requirements
Topic 8
  • Integrate AI Services With Solution Components
  • Set Up Prerequisite Components And Input Datasets To Allow Consumption Of Cognitive Services Apis
Topic 9
  • Design An AI Solution That Includes One Or More Pipelines
  • Design The Compute Infrastructure To Support A Solution
Topic 10
  • Recommend Tools, Technologies, And Processes To Meet Process Flow Requirements
  • Identify Components And Technologies Required To Connect Service Endpoints
Topic 11
  • Integrate AI Models Into Solutions
  • Orchestrate An AI Workflow
  • Manage The Flow Of Data Through Solution Component

Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx

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