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How to Prepare For AI-102: Designing and Implementing an Azure AI Solution Exam

Preparation Guide for AI-102: Designing and Implementing an Azure AI Solution Exam

Introduction

Microsoft has created a track for Azure professionals analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements, to get certified this platform. solution architects translate the vision and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets Microsoft's proficiency standards.

This certification been actually designed for aspirants design and implement AI apps and agents that use Microsoft Azure Cognitive Services.

For this exam candidate having proficiency in using cognitive service APIs to meet business requirements, appropriate AI models and services, automation requirements, data privacy and protection , bot state data , cognitive service output would be an added advantage.

Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work as AI solution architect and prove his knowledge, certification offered by Microsoft. This AI-102 Exam Certification helps a candidate to validates his skills in Azure platform.

In this guide, we will cover the AI-102: Designing and Implementing an Azure AI Solution Certification exam, AI-102: Designing and Implementing an Azure AI Solution Certified professional salary and all aspects of the AI-102: Designing and Implementing an Azure AI Solution Certification.

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

Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:

Microsoft AI-102 Korean Exam Overview:

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 appropriate tools for a solution
• Identify auditing requirements
• Identify which users and groups have access to information and interfaces
• 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 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 pipelines that use AI apps
• Design the integration point between multiple workflows and pipelines
• Select an AI solution that meet cost constraints
• Design a strategy for ingest and egress data
• 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
• Integrate bots and AI solutions
• Design bot services that use Language Understanding (LUIS)
• 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

• Ensure that data adheres to compliance requirements defined by your organization
• Design a content moderation strategy for data usage within an AI solution
• 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

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

Implement an AI workflow

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

Integrate AI services with solution components

• Implement Azure Search in a solution
• 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

Monitor and evaluate the AI environment

• 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
• Maintain an AI solution for continuous improvement

Topics Covered

Exam AI-102 contains five topics each of which is intended to check specific skills.

1. Plan and Manage an Azure Cognitive Services Solution

This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.

2. Implement Computer Vision Solutions

The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.

3. Implement Natural Language Processing Solutions

In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.

4. Implement Knowledge Mining Solutions

In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.

5. Implement Conversational AI Solutions

This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.

Microsoft AI-102 Korean Exam Syllabus Topics: