Exam AI-100: Designing And Implementing An Azure AI Solution Preparation

Microsoft AI-100 Exam

Designing and Implementing an Azure AI Solution
What is the Microsoft AZ-203 Exam?

Microsoft AI-100 Exam -  Everything You Need To Know

Microsoft offers a sizeable certification exam program that is designed to verify the knowledge and skills of professionals in the field of cloud, mobility, data, productivity, app builder and business applications. The Microsoft Certification is the badge of honor and industry-recognized qualification. After the successful completion of Microsoft Certification you can pursue a rewarding career in your chosen field.
Now we talk about the Microsoft AI-300 exam or Designing and implementing an Azure Solution. This exam is designed to verify the skills of the candidate in AI solutions. You will learn to analyze the requirements for AI solutions, technologies, recommend appropriate tools, different possible solutions that meet scalability and performance requirements.
Exam Code AI-100
Exam Name Designing and Implementing an Azure AI Solution
Exam Registration $165 USD
Exam Questions format Multiple Formats
Exam Languages English, Japanese, Chinese (Simplified) and Korean
Retirement Data None

What Skills are Measured with Microsoft AI-100 Exam?

With the Microsoft AI-100 Exam or Designing and Implementing an Azure AI Solution certification exam the following skills are measured.
  1. Analyze solution requirements (25-30%)
    • Recommend Cognitive Services APIs to meet business requirements
    • Map security requirements to tools, technologies, and processes
    • Select the software, services, and storage required to support a solution
  2. Design AI solutions (40-45%)
    • Design solutions that include one or more pipelines
    • Design solutions that use Cognitive Services
    • Design solutions that implement the Bot Framework
    • Design the compute infrastructure to support a solution
    • Design for data governance, compliance, integrity, and security
  3. Implement and monitor AI solutions (25-30%)
    • Implement an AI workflow
    • Integrate AI services with solution components
    • Monitor and evaluate the AI environment
What are the career opportunities after passing the Microsoft AI-100 Exam?
The Microsoft AI-100 exam is a career oriented certification exam that offers multiple careers and personal benefit for the successful candidates. You will get an opportunity to recognize your technical skills, knowledge and greater opportunities for career advancement. Currently, the following jobs are available in the market.
  1. AI Data Engineer Azure
  2. Azure Solutions Architect
  3. Azure Solutions Provider
  4. Senior Data Engineer
  5. Data Scientist
The average estimate salary of an AI Data Engineer is $172,000.

How you can start Microsoft AZ-203 Exam Preparation?

 To pass the Microsoft AI-100 Exam is not an easy task you have to put extra time, efforts and invest money to pass this challenging exam. At CertificationGenie you will find Microsoft AI-100 Exam dumps that will ace your Designing and Implementing an Azure AI Solution exam. Download the free demo of Microsoft AI-100 Exam Questions and check the best feature of our Microsoft AI-100 Exam dumps and start preparation.

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Exam Detail

Exam Name: Designing and Implementing an Azure AI Solution
Vendor Name: Microsoft
Exam Certification: Azure AI Engineer Associate
Exam Language: English
Exam Technologies:

Azure, Bot Service, Cognitive Services, Machine Learning Service, Machine Learning Studio, Search

Exam Topics: Analyze Solution Requirements/ Identify Storage Solutions| Identify The Appropriate Storage Capacity, Storage Types And Storage Locations For A Solution| Recommend Tools, Technologies, And Processes To Meet Process Flow Requirements/ Identify Components And Technologies Required To Connect Service Endpoints| Map Security Requirements To Tools, Technologies, And Processes/ Determine Which Users And Groups Have Access To Information And Interfaces| Identify Appropriate Tools For A Solution/ Identify Auditing Requirements| Select Software And Services Required To Support The Solution/ Identify Appropriate Services/Tools For The Solution| Design An AI Solution That Includes One Or More Pipelines/ Design The Compute Infrastructure To Support A Solution| Design Intelligent Edge Solutions/ Design Data Governance/ Design Solutions That Adhere To Cost Constraints| Integrate AI Models Into Solutions/ Orchestrate An AI Workflow/ Manage The Flow Of Data Through Solution Component| Integrate AI Services With Solution Components/ Set Up Prerequisite Components And Input Datasets To Allow Consumption Of Cognitive Services Apis| Integrate Intelligent Edge With Solutions/ Design Pre-Processing And Processing Strategy For Iot Data| Deploy And Manage Solutions/ Provision Required Cloud, On-Premises, And Hybrid Environments| Validate Solutions To Ensure Compliance With Data Privacy And Security Requirements/ Monitor And Evaluate The AI Environment| Identify Differences Between Kpis And Reported Metrics And Determine Root Causes For Differences

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