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Introduction to AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.

This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.

It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.

After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.

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Topics of AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates should apprehend the examination topics before they begin of preparation. because it'll extremely facilitate them in touch the core. Our AI-102 exam dumps will include the following topics:

1. Analyze solution requirements (25-30%)

Recommend Cognitive Services APIs to meet business requirements

• Select the appropriate data processing technologies
• Identify components and technologies required to connect service endpoints
• Select the processing architecture for a solution
• Identify automation requirements
• Select the appropriate AI models and services

Map security requirements to tools, technologies, and processes

• Identify auditing requirements
• Identify appropriate tools for a solution
• Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
• Identify which users and groups have access to information and interfaces

Select the software, services, and storage required to support a solution

• Identify integration points with other Microsoft services
• Identify appropriate services and tools for a solution
• Identify storage required to store logging, bot state data, and Cognitive Services output

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

• Design pipelines that call Azure Machine Learning models
• Select an AI solution that meet cost constraints
• Define an AI application workflow process
• Design the integration point between multiple workflows and pipelines
• Design a strategy for ingest and egress data
• Design pipelines that use AI apps

Design solutions that uses Cognitive Services

• Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs

Design solutions that implement the Bot Framework

• Integrate bots with Azure app services and Azure Application Insights
• Design bot services that use Language Understanding (LUIS)
• Integrate bots and AI solutions
• Design bots that integrate with channels

Design the compute infrastructure to support a solution

• Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
• Select a compute solution that meets cost constraints
• Identify whether to create a GPU, FPGA, or CPU-based solution

Design for data governance, compliance, integrity, and security

• Design a content moderation strategy for data usage within an AI solution
• Ensure that data adheres to compliance requirements defined by your organization
• Ensure appropriate governance of data
• Design strategies to ensure that the solution meets data privacy regulations and industry standards
• Define how users and applications will authenticate to AI services

3. Implement and monitor AI solutions (25-30%)

Implement an AI workflow

• Implement data logging processes
• Create solution endpoints
• Develop streaming solutions
• Define and construct interfaces for custom AI services
• Develop AI pipelines
• Manage the flow of data through the solution components

Integrate AI services with solution components

• Implement Azure Search in a solution
• Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs
• Configure integration with Cognitive Services
• Configure prerequisite components to allow connectivity to the Bot Framework

Monitor and evaluate the AI environment

• Identify the differences between KPIs, reported metrics, and root causes of the differences
• Recommend changes to an AI solution based on performance data
• Monitor AI components for availability
• Maintain an AI solution for continuous improvement
• Identify the differences between expected and actual workflow throughput

In the past few years, Designing and Implementing a Microsoft Azure AI Solution certification has become an influenced IT technology skill. The person who qualified with Designing and Implementing a Microsoft Azure AI Solution certification may have more opportunity in their future life. You can seek for a better job with incredible salary. Your personal ability improved by studying from the related IT information will bring you much benefit. Such as, you will be adored by other people and build a good and professional personal image in your social circle. However, how to pass the Designing and Implementing a Microsoft Azure AI Solution exam test quickly and simply? I think our Microsoft Designing and Implementing a Microsoft Azure AI Solution can help you solve this problem quickly. We provide Designing and Implementing a Microsoft Azure AI Solution actual study guide to help you pass the exam successfully.

Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam

The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102