How to study the AI-102: Designing and Implementing an Azure AI Solution Exam

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Microsoft AI-102 Exam Syllabus Topics:

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

Software Version

The software version of our AI-102 study engine is designed to simulate a real exam situation. You can install it to as many computers as you need as long as the computer is in Windows system. And our software of the AI-102 training material also allows different users to study at the same time. It's economical for a company to buy it for its staff. Friends or workmates can also buy and learn with it together. With our software of AI-102 guide exam: Designing and Implementing a Microsoft Azure AI Solution, you can practice and test yourself just like you are in a real exam. The results of your test will be analyzed and a statistics will be presented to you. So you can see how you have done and know which kinds of questions of the AI-102 exam are to be learned more.

For more info read reference:

microsoft learning site AI-102 Skills measured Publish a Machine Learning Experiment with Microsoft Azure Machine Learning Studio Process and translate speech with Azure Cognitive Speech Services

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
• Select the appropriate data processing technologies
• 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 storage required to store logging, bot state data, and Cognitive Services output
• Identify appropriate services and tools for a solution

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
• Define an AI application workflow process
• Design a strategy for ingest and egress data
• Select an AI solution that meet cost constraints
• 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 and AI solutions
• Design bot services that use Language Understanding (LUIS)
• Design bots that integrate with channels
• Integrate bots with Azure app services and Azure Application Insights

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

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

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

Implement an AI workflow

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

Integrate AI services with solution components

• Configure prerequisite components to allow connectivity to the Bot Framework
• 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

Monitor and evaluate the AI environment

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

PDF Version

The PDF version of our AI-102 guide exam: Designing and Implementing a Microsoft Azure AI Solution is prepared for you to print it and read it everywhere. It is convenient for you to see the answers to the questions and remember them. After you buy the PDF version of our study material, you will get an E-mail form us in 5 to 10 minutes after payment. Then you can click the link in the E-mail and download your AI-102 study engine. You can download it as many times as you need. Also there is no limit on which computer you want to send it to. Once any new question is found, we will send you a link to download a new version of the AI-102 training materials. So don't worry if you are left behind the trend. Experts in our company won't let this happen.