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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

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

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

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

Design the compute infrastructure to support a solution

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

Design for data governance, compliance, integrity, and security

• Ensure that data adheres to compliance requirements defined by your organization
• Design a content moderation strategy for data usage within an AI solution
• 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
• Develop AI pipelines
• Create solution endpoints
• Manage the flow of data through the solution components
• Define and construct interfaces for custom AI services
• Develop streaming solutions

Integrate AI services with solution components

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

Monitor and evaluate the AI environment

• Identify the differences between expected and actual workflow throughput
• Maintain an AI solution for continuous improvement
• 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

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

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Exam Details

Speaking of the exam details, the test will contain from 40 to 60 questions of various types which you need to complete within 100 or 120 minutes (depends on the inclusion of labs). To pass the exam you need to schedule the test on the PearsonVUE platform, pay an exam fee which is currently $165, and score at least 700 points or more out of 1000. And, of course, the knowledge of exam topics is a must.

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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.

Microsoft AI-102 Exam Syllabus Topics: