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AI-102 Exam Study Guide: Azure AI Engineer Associate Certification

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Updated – 05/11/2023 – The exam guide below shows the major changes that will be implemented starting on October 31, 2023. The study guide has been updated to reflect the new objectives and exam topic weights added and removed by Microsoft Learning.

Updated – 20/07/2023 – The exam study guide below includes a new Free practice assessment for the AI-102 certification.

In this article, we will share with you how to prepare and pass the AI-102 exam — Azure AI Engineer Associate Certification successfully.

Introduction

As everyone is exploring Artificial Intelligence and looking to increase their skills, I thought I would try and lend a hand and create a study guide for the AI-102 exam that gets you the Azure AI Engineer Associate certification.

Microsoft is evolving its e-learning programs to help you and your career keep pace with today’s demanding IT environments. The new updated role-based certifications will help you to keep pace with today’s business requirements. Microsoft Learning is constantly evolving its e-learning program to better offer what you need to skill up, prove your expertise to employers and peers, and get the recognition—and opportunities you’ve earned.

In February 2021, Microsoft announced a new certification exam that focus on Azure AI solutions which replaced Exam AI-100 (retired on June 30, 2021). The Exam AI-102 is the only exam required to earn an Azure AI Engineer Associate certification.

Related: Conquer the AI-050 course and revolutionize your skills in Developing Generative AI Solutions with Azure OpenAI service!

Exam Target Audience

The role of Microsoft Azure AI engineers entails the building, administration, and implementation of AI solutions that leverage the capabilities of Azure Cognitive Services and Azure services. Their responsibilities encompass all stages of AI solution development, including requirement gathering, design, development, deployment, integration, maintenance, performance optimization, and monitoring.

These professionals collaborate closely with solution architects to translate their vision into reality. They also work alongside data scientists, engineers, IoT specialists, infrastructure administrators, and other software developers to construct comprehensive end-to-end AI solutions.

Azure AI engineers possess expertise in utilizing programming languages such as Python or C# and are adept at leveraging REST-based APIs and software development kits (SDKs) to construct secure solutions for image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI on the Azure platform. They are well-versed in various methods of implementing AI solutions and possess a comprehensive understanding of the components that constitute the Azure AI portfolio, as well as the available data storage options. Furthermore, Azure AI engineers demonstrate a deep understanding of responsible AI principles and are proficient in their applications.

Importance of AI-102 Certification

The Microsoft AI-102 certification holds paramount importance for professionals seeking to enrich their knowledge and proficiency in artificial intelligence while advancing their careers.

The Importance of AI-102 Certification
The Importance of AI-102 Certification

This certification validates candidates’ skills in designing and implementing AI solutions using Microsoft technologies and tools. Globally recognized, the certification showcases to employers and clients that the certified expert possesses the ability and knowledge to develop and deploy AI solutions using Azure services.

Obtaining the certification can boost the professional’s credibility, opening doors to better job opportunities and higher salaries. The certification program necessitates learning about the latest tools and technologies in AI development, empowering candidates to stay ahead of the curve and remain competitive in the job market.

Keeping up with current developments and trends in AI is crucial, and the certification facilitates professionals in achieving this goal. The certification offers a structured learning path for those interested in AI, serving as a benchmark for measuring their progress and skill level. Designed to cater to both technical and business professionals, this certification is a versatile and valuable accreditation to pursue.

AI-102 Prerequisites Knowledge

To successfully benefit from this certification, you must have a working knowledge of the Microsoft Azure platform. Please note that there is no content around Azure administration tasks or how to navigate the Azure platform. You are also expected to have completed Azure Fundamentals and Azure AI Fundamentals training, or equivalent before undertaking this certification.

Also, the following are other areas that are considered critical knowledge to succeed in this exam:

• Familiarity with Azure and the Azure portal.
• Familiarity with Visual Studio Code.
• Familiarity with C# and Python.
• Familiarity with REST programming principles and JSON.
• Familiarity with Azure Cognitive Services, Azure Bot Service, and Azure Cognitive Search.

If you have no previous programming experience, it’s recommended to complete the Take Your First Steps with C# or Take Your First Steps with Python learning path before starting the AI-102 exam preparation.

AI-102 Exam Preparation

How do you prepare for the AI-102 exam?

We want to share with you how to prepare and pass the AI-102: Designing and Implementing a Microsoft Azure AI Solution exam successfully to obtain the Azure AI Engineer Associate certification.

The Journey to Microsoft Certified: Azure AI Engineer Associate
The Journey to Microsoft Certified: Azure AI Engineer Associate (image Source – Microsoft)

Azure OpenAI Service provides access to OpenAI’s powerful large language models such as ChatGPT, GPT, Codex, and Embeddings models. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio.

The AI-102 is a 2 hours exam, but within that two hours, it includes 20 minutes for survey time. The actual exam is only one hour and 40 minutes. I had 49 questions in total including 1 case study with 6 questions and without performance-based testing (PBT) lab questions. However, you will need to choose your preferred coding language (Python or C#) at the beginning of the exam for drag-and-drop questions and to understand the code snippet-type questions.

Updated on 21/11/2023 – I am so happy and grateful now that I passed the AI-102 Exam: Designing and Implementing a Microsoft Azure AI Solution with a passing score (821) as shown in the report below! I want to mention that the exam is tough, you need to prepare very well. I managed to answer all of the 49 questions within 1 hour and 40 minutes. The passing score for the AI-102 exam is 70%, so 700 out of 1,000.

Passing AI-102 Exam - Microsoft Certified: Azure AI Engineer Associate
Passing AI-102 Exam – Microsoft Certified: Azure AI Engineer Associate

When you do this exam, take your time on every question because you have a fair amount of time. The questions are relatively short in type, so you don’t have a huge amount of text to read. Don’t forget to use the “Microsoft Learnopen-book capability during the exam, so you access the live documentation and cross-check your answers.

Skills measured on the AI-102 exam

This exam measures your ability to accomplish the technical topics listed below based on the latest update from Microsoft.

Links to relevant reading from the official Microsoft Learn documentation for each skill tested are listed below to help you prepare for this exam:

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

Learning Path

Implement decision support solutions (10–15%)

Create decision-support solutions for data monitoring and anomaly detection

  • Implement a univariate anomaly detection solution with Azure AI Anomaly Detector
  • Implement a multivariate anomaly detection solution Azure AI Anomaly Detector
  • Implement a data monitoring solution with Azure AI Metrics Advisor

Create decision-support 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 a content personalization solution with Azure AI Personalizer

Learning Path

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

Learning Path

Implement natural language processing solutions (30–35%)

Analyze text by using Azure AI-Language

  • Extract key phrases
  • Extract entities
  • Determine the sentiment of the text
  • Detect the language used in the 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

Learning Path

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

Learning Path

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

Learning Path

AI-102 Training Labs

These hands-on lab exercises support the official Microsoft course AI-102 Designing and Implementing a Microsoft Azure AI Solution and the equivalent self-paced modules on Microsoft Learn. The exercises are designed to accompany the learning materials and enable you to practice using the technologies they describe.

To complete these exercises, please note that you’ll require a Microsoft Azure subscription. You can sign up for a free trial at https://azure.microsoft.com.

AI Engineer Exercises

Exercises

AI-102 Video Training

If  you are interested in preparing for this exam using video training, then I highly recommend checking the following resources:

> Pluralsight: If you have access to a Pluralsight Learning platform, then I highly recommend going through the following exam preparation learning path: Microsoft Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution (10 hours).

> YouTube: AI-102 Study Cram – Azure AI Engineer Associate Certification by John Savill (2 hours).

> Udemy: AI-102 Microsoft Azure AI Solution Complete Exam Prep by Scott Duffy (7.5 hours).

AI-102 Exam Readiness

The Microsoft Learn exam readiness zone is a team of experts who share valuable insights, techniques, and strategies to help you prepare effectively for your Microsoft Certification exam.

The comprehensive exam preparation videos will assist you in identifying the key areas of knowledge and skills assessed in the AI-102 exam, as well as guide you on how to allocate your study time efficiently. Each video segment below corresponds to a significant topic covered in the latest AI-102 exam, and the trainer highlights objectives that many test takers typically find challenging.

1) Preparing for AI-102 – Plan and manage an Azure AI solution.

2) Preparing for AI-102 – Implement image and video processing solutions.

3) Preparing for AI-102 – Implement natural language processing solutions.

4) Preparing for AI-102Implement knowledge mining solutions.

5) Preparing for AI-102 – Implement conversational AI solutions.

These free videos include illustrative sample questions and detailed explanations of the answers. We recommend watching these videos once you have completed your training or gained some practice, although you are welcome to view them at any stage of your certification journey. Additionally, they provide additional resources to further aid you in your AI-102 exam preparation.

AI-102 Practice Test

If you wish to validate your skills before taking the real exam, I highly encourage you to purchase the following practice test:

AI-102: Designing and Implementing an Azure AI Solution Microsoft Certification Practice Test. The MeasureUp AI-102: Designing and Implementing a Microsoft Azure AI Solution practice test from mind hub is designed to help you prepare for and pass the Microsoft AI-102 exam. This exam is aimed at candidates who want to validate their skills.

You should know C# or Python and be able to use REST-based APIs and SDKs. You should be able to participate in all phases of AI solutions development, as well as to work with solution architects to translate their vision and to work with other experts to build complete end-to-end AI solutions.

The AI-102 test contains 144 questions and covers the following objectives:

  • Plan and manage an Azure Cognitive Services solution – 23 questions.
  • Implement Computer Vision solutions – 36 questions.
  • Implement natural language processing solutions – 29 questions.
  • Implement knowledge mining solutions – 25 questions.
  • Implement conversational AI solutions – 31 questions.

AI-102 Free Practice Assessment

Are you preparing for the AI-102 certification exam? Microsoft just announced Practice Assessments on Microsoft Learn, the newest free exam preparation resource that allows you to assess your knowledge and fill knowledge gaps so that you are better prepared to take the AI-102 certification exam.

The following assessment provides you with an overview of the style, wording, and difficulty of the questions you’re likely to experience on the exam. Through this assessment, you can assess your readiness, determine where additional preparation is needed, and fill knowledge gaps bringing you one step closer to the likelihood of passing your AI-102 exam.

> Take now the Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution Practice Assessment (50 questions).

Prepare for your certification exam by assessing your knowledge through Practice Assessments, which are free and can be attempted multiple times. These assessments are created and regularly updated by the same team that develops the official certification exams.

You can access practice assessments on Microsoft Learn by signing in or creating an account. The score report for each question includes the answer, rationale, and links to additional information.

To be better prepared for the AI-102 exam, aim to achieve a score of 80% or higher in multiple attempts.

Schedule AI-102 Exam

Once you are ready, click Schedule exam here and take it online from the comfort of your home/office with proctor supervision.

Schedule Your AI-102 Exam Today
Schedule Your AI-102 Exam Today

If you are planning to take the AI-102 exam… I wish you all the best and Happy Studying!!!

AI-102 Exam FAQs

What is the passing score for the AI-102 exam?

The passing score for the AI-102 exam is 700 out of 1000 points.

How many questions are there in the AI-102 exam?

The AI-102 exam consists of approximately 40-60 questions, and the total time for the AI-102 exam is 130 minutes (2.10 hours)

Are there any prerequisites for the Azure AI Engineer Associate Certification?

Yes, you should have some prior experience with Azure services and basic knowledge of AI concepts.

Can I retake the AI-102 exam if I fail?

Yes, you can retake the exam after waiting for 24 hours from your first attempt.

Are the AI-102 exam objectives subject to change?

Yes, Microsoft may update the exam objectives to align with the evolving industry trends.

Is hands-on experience necessary for passing the AI-102 exam?

Hands-on experience with Azure AI services and tools will significantly improve your chances of passing the exam.

Conclusion

The Microsoft AI-102 certification exam holds great significance for professionals aiming to demonstrate their proficiency in designing and implementing Azure AI solutions. It presents a great challenge, demanding a profound grasp of Azure services, AI technologies, and data science principles. Nevertheless, you can enhance the likelihood of success by leveraging appropriate study materials, resources, and strategic approaches shared in this article.

Attaining the Microsoft AI-102 certification enables professionals to propel their careers forward, showcase their expertise to employers and clients, and gain a competitive edge in the job market.

Other Microsoft Azure Exam Study Guides

Are you interested in another Azure certification exam? I highly encourage you to check out the following Azure exam study guides:

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Thank you for reading my blog.

If you have any questions or feedback, please leave a comment.

-Charbel Nemnom-

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About the Author
Charbel Nemnom
Charbel Nemnom is a Senior Cloud Architect with 20+ years of IT experience. As a Swiss Certified ICT Security Expert, CCSP, CISM, MVP, and MCT, he excels in optimizing mission-critical enterprise systems. His extensive practical knowledge spans complex system design, network architecture, business continuity, and cloud security, establishing him as an authoritative and trustworthy expert in the field. Charbel frequently writes about Cloud, Cybersecurity, and IT Certifications.
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2 thoughts on “AI-102 Exam Study Guide: Azure AI Engineer Associate Certification”

Leave a comment...

  1. Thank you for the detailed break-down, Charbel.

    I know that you’ve updated this post in line with the latest updates from Microsoft, but do you know if either of the two recommended courses (Pluralsight and Scott Duffy’s Udemy course) have been updated?

  2. Hello Abhy, thanks for the comment and feedback!
    Yes, the article was updated to reflect the latest changes by Microsoft, as well as after I passed the AI-102 exam recently.
    The courses that I’ve noted (Pluralsight and Scott Duffy’s Udemy) are not been updated to reflect the October 2023 update, but this could change soon.
    Good Luck!

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