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Study guide for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution

Purpose of this document

This study guide should help you understand what to expect on the exam and includes a summary of the topics the exam might cover and links to additional resources. The information and materials in this document should help you focus your studies as you prepare for the exam.

Useful links Description
Review the skills measured as of March 28, 2024 This list represents the skills measured AFTER the date provided. Study this list if you plan to take the exam AFTER that date.
Review the skills measured prior to March 28, 2024 Study this list of skills if you take your exam PRIOR to the date provided.
Change log You can go directly to the change log if you want to see the changes that will be made on the date provided.
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Exam scoring and score reports A score of 700 or greater is required to pass.
Exam sandbox You can explore the exam environment by visiting our exam sandbox.
Request accommodations If you use assistive devices, require extra time, or need modification to any part of the exam experience, you can request an accommodation.
Take a free Practice Assessment Test your skills with practice questions to help you prepare for the exam.

Updates to the exam

Our exams are updated periodically to reflect skills that are required to perform a role. We have included two versions of the Skills Measured objectives depending on when you are taking the exam.

We always update the English language version of the exam first. Some exams are localized into other languages, and those are updated approximately eight weeks after the English version is updated. While Microsoft makes every effort to update localized exams as noted, there may be times when the localized versions of an exam are not updated on this schedule. Other available languages are listed in the Schedule Exam section of the Exam Details webpage. If the exam isn't available in your preferred language, you can request an additional 30 minutes to complete the exam.

Note

The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam.

Note

Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used.

Skills measured as of March 28, 2024

Audience profile

As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.

Your responsibilities include participating in all phases of AI solutions development, including:

  • Requirements definition and design

  • Development

  • Deployment

  • Integration

  • Maintenance

  • Performance tuning

  • Monitoring

You work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:

  • Build complete and secure end-to-end AI solutions.

  • Integrate AI capabilities in other applications and solutions.

As an Azure AI engineer, you have experience developing solutions that use languages such as:

  • Python

  • C#

You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should:

  • Understand the components that make up the Azure AI portfolio and the available data storage options.

  • Be able to apply responsible AI principles.

Skills at a glance

  • Plan and manage an Azure AI solution (15–20%)

  • Implement content moderation solutions (10–15%)

  • Implement computer vision solutions (15–20%)

  • Implement natural language processing solutions (30–35%)

  • Implement knowledge mining and document intelligence solutions (10–15%)

  • Implement generative AI solutions (10–15%)

Plan and manage an Azure AI solution (15–20%)

Select the appropriate Azure AI service

  • Select the appropriate service for a computer vision solution

  • Select the appropriate service for a natural language processing solution

  • Select the appropriate service for a speech solution

  • Select the appropriate service for a generative AI solution

  • Select the appropriate service for a document intelligence solution

  • Select the appropriate service for a knowledge mining solution

Plan, create and deploy an Azure AI service

  • Plan for a solution that meets Responsible AI principles

  • Create an Azure AI resource

  • Determine a default endpoint for a service

  • Integrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipeline

  • Plan and implement a container deployment

Manage, monitor, and secure an Azure AI service

  • Configure diagnostic logging

  • Monitor an Azure AI resource

  • Manage costs for Azure AI services

  • Manage account keys

  • Protect account keys by using Azure Key Vault

  • Manage authentication for an Azure AI Service resource

  • Manage private communications

Implement content moderation solutions (10–15%)

Create solutions for content delivery

  • Implement a text moderation solution with Azure AI Content Safety

  • Implement an image moderation solution with Azure AI Content Safety

Implement computer vision solutions (15–20%)

Analyze images

  • Select visual features to meet image processing requirements

  • Detect objects in images and generate image tags

  • Include image analysis features in an image processing request

  • Interpret image processing responses

  • Extract text from images using Azure AI Vision

  • Convert handwritten text using Azure AI Vision

Implement custom computer vision models by using Azure AI Vision

  • Choose between image classification and object detection models

  • Label images

  • Train a custom image model, including image classification and object detection

  • Evaluate custom vision model metrics

  • Publish a custom vision model

  • Consume a custom vision model

Analyze videos

  • Use Azure AI Video Indexer to extract insights from a video or live stream

  • Use Azure AI Vision Spatial Analysis to detect presence and movement of people in video

Implement natural language processing solutions (30–35%)

Analyze text by using Azure AI Language

  • Extract key phrases

  • Extract entities

  • Determine sentiment of text

  • Detect the language used in text

  • Detect personally identifiable information (PII) in text

Process speech by using Azure AI Speech

  • Implement text-to-speech

  • Implement speech-to-text

  • Improve text-to-speech by using Speech Synthesis Markup Language (SSML)

  • Implement custom speech solutions

  • Implement intent recognition

  • Implement keyword recognition

Translate language

  • Translate text and documents by using the Azure AI Translator service

  • Implement custom translation, including training, improving, and publishing a custom model

  • Translate speech-to-speech by using the Azure AI Speech service

  • Translate speech-to-text by using the Azure AI Speech service

  • Translate to multiple languages simultaneously

Implement and manage a language understanding model by using Azure AI Language

  • Create intents and add utterances

  • Create entities

  • Train, evaluate, deploy, and test a language understanding model

  • Optimize a language understanding model

  • Consume a language model from a client application

  • Backup and recover language understanding models

Create a question answering solution by using Azure AI Language

  • Create a question answering project

  • Add question-and-answer pairs manually

  • Import sources

  • Train and test a knowledge base

  • Publish a knowledge base

  • Create a multi-turn conversation

  • Add alternate phrasing

  • Add chit-chat to a knowledge base

  • Export a knowledge base

  • Create a multi-language question answering solution

Implement knowledge mining and document intelligence solutions (10–15%)

Implement an Azure AI Search solution

  • Provision an Azure AI Search resource

  • Create data sources

  • Create an index

  • Define a skillset

  • Implement custom skills and include them in a skillset

  • Create and run an indexer

  • Query an index, including syntax, sorting, filtering, and wildcards

  • Manage Knowledge Store projections, including file, object, and table projections

Implement an Azure AI Document Intelligence solution

  • Provision a Document Intelligence resource

  • Use prebuilt models to extract data from documents

  • Implement a custom document intelligence model

  • Train, test, and publish a custom document intelligence model

  • Create a composed document intelligence model

  • Implement a document intelligence model as a custom Azure AI Search skill

Implement generative AI solutions (10–15%)

Use Azure OpenAI Service to generate content

  • Provision an Azure OpenAI Service resource

  • Select and deploy an Azure OpenAI model

  • Submit prompts to generate natural language

  • Submit prompts to generate code

  • Use the DALL-E model to generate images

  • Use Azure OpenAI APIs to submit prompts and receive responses

Optimize generative AI

  • Configure parameters to control generative behavior

  • Apply prompt engineering techniques to improve responses

  • Use your own data with an Azure OpenAI model

  • Fine-tune an Azure OpenAI model

Study resources

We recommend that you train and get hands-on experience before you take the exam. We offer self-study options and classroom training as well as links to documentation, community sites, and videos.

Study resources Links to learning and documentation
Get trained Choose from self-paced learning paths and modules or take an instructor-led course
Find documentation Azure AI services
Azure AI Vision
Azure AI Video Indexer
Azure AI Language
Azure AI Speech
Azure AI Search
Azure OpenAI
Azure AI Document Intelligence
Ask a question Microsoft Q&A | Microsoft Docs
Get community support AI - Machine Learning - Microsoft Tech Community
AI - Machine Learning Blog - Microsoft Tech Community
Follow Microsoft Learn Microsoft Learn - Microsoft Tech Community
Find a video The AI Show
Browse other Microsoft Learn shows

Change log

Key to understanding the table: The topic groups (also known as functional groups) are in bold typeface followed by the objectives within each group. The table is a comparison between the two versions of the exam skills measured and the third column describes the extent of the changes.

Skill area prior to March 28, 2024 Skill area as of March 28, 2024 Change
Audience profile No change
Plan and manage an Azure AI solution Plan and manage an Azure AI solution Minor
Select the appropriate Azure AI service Select the appropriate Azure AI service No change
Plan, create and deploy an Azure AI service Plan, create and deploy an Azure AI service No change
Manage, monitor and secure an Azure AI service Manage, monitor, and secure an Azure AI service Minor
Implement decision support solutions Implement content moderation solutions Minor
Create decision support solutions for data monitoring and content delivery Create solutions for content delivery Minor
Implement computer vision solutions Implement computer vision solutions No change
Analyze images Analyze images No change
Implement custom computer vision models by using Azure AI Vision Implement custom computer vision models by using Azure AI Vision No change
Analyze videos Analyze videos No change
Implement natural language processing solutions Implement natural language processing solutions No change
Analyze text by using Azure AI Language Analyze text by using Azure AI Language No change
Process speech by using Azure AI Speech Process speech by using Azure AI Speech No change
Translate language Translate language No change
Implement and manage a language understanding model by using Azure AI Language Implement and manage a language understanding model by using Azure AI Language No change
Create a question answering solution by using Azure AI Language Create a question answering solution by using Azure AI Language No change
Implement knowledge mining and document intelligence solutions Implement knowledge mining and document intelligence solutions No change
Implement an Azure Cognitive Search solution Implement an Azure AI Search solution Minor
Implement an Azure AI Document Intelligence solution Implement an Azure AI Document Intelligence solution Minor
Implement generative AI solutions Implement generative AI solutions No change
Use Azure OpenAI Service to generate content Use Azure OpenAI Service to generate content No change
Optimize generative AI Optimize generative AI No change

Skills measured prior to March 28, 2024

Audience profile

As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.

Your responsibilities include participating in all phases of AI solutions development, including:

  • Requirements definition and design

  • Development

  • Deployment

  • Integration

  • Maintenance

  • Performance tuning

  • Monitoring

You work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:

  • Build complete and secure end-to-end AI solutions.

  • Integrate AI capabilities in other applications and solutions.

As an Azure AI engineer, you have experience developing solutions that use languages such as:

  • Python

  • C#

You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should:

  • Understand the components that make up the Azure AI portfolio and the available data storage options.

  • Be able to apply responsible AI principles.

Skills at a glance

  • Plan and manage an Azure AI solution (15–20%)

  • Implement decision support solutions (10–15%)

  • Implement computer vision solutions (15–20%)

  • Implement natural language processing solutions (30–35%)

  • Implement knowledge mining and document intelligence solutions (10–15%)

  • Implement generative AI solutions (10–15%)

Plan and manage an Azure AI solution (15–20%)

Select the appropriate Azure AI service

  • Select the appropriate service for a computer vision solution

  • Select the appropriate service for a natural language processing solution

  • Select the appropriate service for a decision support solution

  • Select the appropriate service for a speech solution

  • Select the appropriate service for a generative AI solution

  • Select the appropriate service for a document intelligence solution

  • Select the appropriate service for a knowledge mining solution

Plan, create and deploy an Azure AI service

  • Plan for a solution that meets Responsible AI principles

  • Create an Azure AI resource

  • Determine a default endpoint for a service

  • Integrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipeline

  • Plan and implement a container deployment

Manage, monitor and secure an Azure AI service

  • Configure diagnostic logging

  • Monitor an Azure AI resource

  • Manage costs for Azure AI services

  • Manage account keys

  • Protect account keys by using Azure Key Vault

  • Manage authentication for an Azure AI Service resource

  • Manage private communications

Implement decision support solutions (10–15%)

Create decision support solutions for data monitoring and content delivery

  • Implement a data monitoring solution with Azure AI Metrics Advisor

  • Implement a text moderation solution with Azure AI Content Safety

  • Implement an image moderation solution with Azure AI Content Safety

Implement computer vision solutions (15–20%)

Analyze images

  • Select visual features to meet image processing requirements

  • Detect objects in images and generate image tags

  • Include image analysis features in an image processing request Interpret image processing responses

  • Extract text from images using Azure AI Vision

  • Convert handwritten text using Azure AI Vision

Implement custom computer vision models by using Azure AI Vision

  • Choose between image classification and object detection models

  • Label images

  • Train a custom image model, including image classification and object detection

  • Evaluate custom vision model metrics

  • Publish a custom vision model

  • Consume a custom vision model

Analyze videos

  • Use Azure AI Video Indexer to extract insights from a video or live stream

  • Use Azure AI Vision Spatial Analysis to detect presence and movement of people in video

Implement natural language processing solutions (30–35%)

Analyze text by using Azure AI Language

  • Extract key phrases

  • Extract entities

  • Determine sentiment of text

  • Detect the language used in text

  • Detect personally identifiable information (PII) in text

Process speech by using Azure AI Speech

  • Implement text-to-speech

  • Implement speech-to-text

  • Improve text-to-speech by using Speech Synthesis Markup Language (SSML)

  • Implement custom speech solutions

  • Implement intent recognition

  • Implement keyword recognition

Translate language

  • Translate text and documents by using the Azure AI Translator service

  • Implement custom translation, including training, improving, and publishing a custom model

  • Translate speech-to-speech by using the Azure AI Speech service

  • Translate speech-to-text by using the Azure AI Speech service

  • Translate to multiple languages simultaneously

Implement and manage a language understanding model by using Azure AI Language

  • Create intents and add utterances

  • Create entities

  • Train, evaluate, deploy, and test a language understanding model

  • Optimize a language understanding model

  • Consume a language model from a client application

  • Backup and recover language understanding models

Create a question answering solution by using Azure AI Language

  • Create a question answering project

  • Add question-and-answer pairs manually

  • Import sources

  • Train and test a knowledge base

  • Publish a knowledge base

  • Create a multi-turn conversation

  • Add alternate phrasing

  • Add chit-chat to a knowledge base

  • Export a knowledge base

  • Create a multi-language question answering solution

Implement knowledge mining and document intelligence solutions (10–15%)

Implement an Azure Cognitive Search solution

  • Provision a Cognitive Search resource

  • Create data sources

  • Create an index

  • Define a skillset

  • Implement custom skills and include them in a skillset

  • Create and run an indexer

  • Query an index, including syntax, sorting, filtering, and wildcards

  • Manage Knowledge Store projections, including file, object, and table projections

Implement an Azure AI Document Intelligence solution

  • Provision a Document Intelligence resource

  • Use prebuilt models to extract data from documents

  • Implement a custom document intelligence model

  • Train, test, and publish a custom document intelligence model

  • Create a composed document intelligence model

  • Implement a document intelligence model as a custom Azure Cognitive Search skill

Implement generative AI solutions (10–15%)

Use Azure OpenAI Service to generate content

  • Provision an Azure OpenAI Service resource

  • Select and deploy an Azure OpenAI model

  • Submit prompts to generate natural language

  • Submit prompts to generate code

  • Use the DALL-E model to generate images

  • Use Azure OpenAI APIs to submit prompts and receive responses

Optimize generative AI

  • Configure parameters to control generative behavior

  • Apply prompt engineering techniques to improve responses

  • Use your own data with an Azure OpenAI model

  • Fine-tune an Azure OpenAI model