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. |
| How to earn the certification | Some certifications only require passing one exam, while others require passing multiple exams. |
| Certification renewal | Microsoft associate, expert, and specialty certifications expire annually. You can renew by passing a free online assessment on Microsoft Learn. |
| Your Microsoft Learn profile | Connecting your certification profile to Microsoft Learn allows you to schedule and renew exams and share and print certificates. |
| 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