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

Map security requirements to tools, technologies, and processes

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

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

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

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

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

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)
• Design bots that integrate with channels
• Integrate bots and AI solutions

Design the compute infrastructure to support a solution

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

Design for data governance, compliance, integrity, and security

• Define how users and applications will authenticate to AI services
• Design strategies to ensure that the solution meets data privacy regulations and industry standards
• 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

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

Implement an AI workflow

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

Integrate AI services with solution components

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

Monitor and evaluate the AI environment

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

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

Schedule exam

Languages: English, Japanese, Chinese (Simplified), Korean

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: plan and manage an Azure Cognitive Services solutions; implement Computer Vision solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions.

For candidates that are aiming to develop their skills in building, operating, and deploying AI solutions with the help of such services as Azure Applied AI services and Azure Cognitive Services, the best variant is to pass the Microsoft AI-102 exam. This exam is all about designing and applying a Microsoft Azure AI Solution, and leads to getting the Microsoft Certified: Azure AI Engineer Associate certification.

Passing this exam implies that certified candidates are able to participate in all stages of AI solutions development from defining requirements to performance tuning and monitoring. These professionals cooperate with solution architects, as well as with data engineers and scientists, AI developers to show their vision and create comprehensive AI solutions.

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

• This is beta exam.
• 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
• Language: English, Japanese, Chinese (Simplified), Korean.
• Passing Score: 700 / 1000
• Type of Questions: This test format is multiple choice.

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