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

Map security requirements to tools, technologies, and processes

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

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

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

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

• Design the integration point between multiple workflows and pipelines
• Design pipelines that call Azure Machine Learning models
• 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 with Azure app services and Azure Application Insights
• Design bots that integrate with channels
• Integrate bots and AI solutions
• Design bot services that use Language Understanding (LUIS)

Design the compute infrastructure to support a solution

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

Design for data governance, compliance, integrity, and security

• 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
• Define how users and applications will authenticate to AI services
• Ensure appropriate governance of data
• Design a content moderation strategy for data usage within an AI solution

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

Implement an AI workflow

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

Integrate AI services with solution components

• Implement Azure Search in a solution
• Configure prerequisite components to allow connectivity to the Bot Framework
• 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

• Maintain an AI solution for continuous improvement
• Identify the differences between expected and actual workflow throughput
• Monitor AI components for availability
• Recommend changes to an AI solution based on performance data
• 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

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

Preparation of certification exams could be covered with two resource types . The first one are the study guides, reference books and study forums that are elaborated and appropriate for building information from ground up. Apart from them video tutorials and lectures are a good option to ease the pain of through study and are relatively make the study process more interesting nonetheless these demand time and concentration from the learner. Smart candidates who wish to create a solid foundation altogether examination topics and connected technologies typically mix video lectures with study guides to reap the advantages of each but practice exams or practice exam engines is one important study tool which goes typically unnoted by most candidates. Practice exams are designed with our experts to make exam prospects test their knowledge on skills attained in course, as well as prospects become comfortable and familiar with the real exam environment. Statistics have indicated exam anxiety plays much bigger role of students failure in exam than the fear of the unknown. RealVCE expert team recommends preparing some notes on these topics along with it don't forget to practice AI-102 exam dumps which had been written by our expert team, each of these can assist you loads to clear this exam with excellent marks.

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

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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