The AI-102 Microsoft Azure AI Engineer Associate certification exam is designed for individuals with experience designing, developing, and deploying AI solutions on Microsoft Azure. The exam will assess your technical abilities in implementing solutions leveraging various Azure AI services based on specific requirements. Prior experience in software development, data science, or AI solution building will be beneficial in understanding the concepts and services effectively.

The content of the exam will test your ability to perform the following:

• Plan and manage an Azure AI solution

• Implement generative AI solutions

• Implement an agentic solution

• Implement computer vision solutions

• Implement natural language processing solutions

• Implement knowledge mining and information extraction solutions

For more information about the AI-102 exam, you can check out this exam skills outline. This study guide will provide comprehensive review materials to help you pass the exam successfully.

Study Materials

Before attempting the Microsoft Certified: Azure AI Engineer Associate exam (AI-102), it is highly advised to go through these study materials. These resources are specifically designed to aid you in grasping the intricate concepts and services that will be addressed in the exam.

1. Microsoft Learn – This website offers a variety of learning paths for different Microsoft certifications. For the AI-102 certification exam, you can focus on the following topics:
   • AI-102 Overview
   • AI-102 official study guide
   • Learning paths and modules related to Azure AI services
2. Azure Documentation – The documents provide a comprehensive set of resources, including overviews, tutorials, examples, and how-to guides, which can help you understand various Azure AI services in depth. Focus on the documentation for:
   • Azure AI Vision
   • Azure AI Language
   • Speech service
   • Azure AI Search
   • Azure Bot Service
   • Azure Machine Learning
3. Azure Blog – To stay up-to-date on the latest technologies and offerings from Microsoft Azure, you can subscribe to their newsletter and specifically follow updates related to Azure AI services.
4. Azure FAQs – The Azure documentation includes comprehensive FAQ sections that answer common questions about Azure AI services, use cases, pricing, and comparisons. You can usually find FAQ links within the overview pages of each service (e.g., for Vision: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/computer-vision-faq).
5. Azure Free Account – The Azure portal offers a trial that gives you hands-on experience with Azure services. Utilize free tiers and credits to experiment with the Azure AI services covered in the exam.
6.  Tutorials Dojo’s Azure Cheat Sheets – with the help of our cheat sheets, you can easily understand the information found in the Azure documentation. These are presented in bullet point format to highlight the important concepts.
7. Tutorials Dojo’s AZ-102 Microsoft Azure AI Engineer Associate Practice Exams – our practice exams are consistently ranked among the best in the market. Each question comes with comprehensive explanations that will help you understand the crucial concepts you need to succeed in your Microsoft Azure certification exam on your first attempt

Azure Services to Focus On

Your primary source of information when studying for the AI-102 certification exam is the Azure documentation. To comprehend the different scenarios in the exam, you should have a thorough understanding of the following services:

• Azure AI Vision – Deep understanding of Image Analysis, Object Detection, Optical Character Recognition (OCR) , and Face service for analyzing people’s movement and interactions in video streams.
• Azure AI Language – Thorough knowledge of Sentiment Analysis and Opinion Mining, Key Phrase Extraction, Language Detection, Named Entity Recognition (NER), Text Analytics for health, Custom Text Classification, Custom Named Entity Recognition, and Conversational Language Understanding (CLU) for building conversational interfaces. Familiarity with the transition from Language Understanding (LUIS) to CLU is also essential.
• Speech service – Comprehensive understanding of Speech-to-Text (audio transcription, customization options), Text-to-Speech (voice selection, SSML), Speech Translation, and Speaker Recognition (identification and verification of speakers).
• Azure AI Search – Expertise in creating and managing search services, defining indexes (fields, data types, indexers), building skillsets for AI enrichment (leveraging both built-in cognitive skills and custom skills), understanding knowledge stores for projecting enriched data, and crafting effective search queries.
• Azure Bot Service – Proficiency in creating, deploying, and managing bots using the Bot Framework SDK. Understanding integration with Language service (CLU/LUIS) for natural language understanding, Speech service for voice interactions, and QnA Maker for knowledge base integration. Knowledge of different bot channels is also relevant.
• Azure Machine Learning – While not the central focus, understand its role in the AI lifecycle, particularly for custom model development, deployment (including managed endpoints and containerization), and management. Familiarity with concepts like data labeling, feature engineering, and the overall ML workflow is beneficial.
• Azure OpenAI Service – Awareness of its capabilities in generating human-like text, code, and images using models like GPT, Codex, and DALL-E. Understand potential use cases in content creation, summarization, and conversational AI.
• Azure Storage Services – Understanding different storage account types (Blob, Data Lake Storage), storage tiers, and methods for data ingestion and management for AI workloads.
• Azure Cognitive Services Resource Management – Knowledge of creating and managing Azure AI Services multi-service accounts and single-service accounts, understanding endpoints and API keys, and implementing security.
• Azure Security Services – Familiarity with securing AI solutions using Azure Active Directory (Azure AD), Role-Based Access Control (RBAC), network security (firewalls, virtual networks, private endpoints), and data encryption.
• Azure Monitor – Understanding how to monitor the health, performance, and usage of your AI services using metrics, logs, and alerts.

We suggest that you check out Tutorials Dojo’s Azure Cheat Sheets, which provides bullet-point summaries of the most important concepts on different Azure AI services and related Azure functionalities. Make sure to spend ample time reviewing the official Azure documentation for each of these services to gain a comprehensive understanding for the AI-102 exam.

Validate Your Knowledge

If you feel confident after going through the suggested materials above, it’s time to put your knowledge of different Azure concepts and services to the test. For top-notch practice exams, consider using the Tutorials Dojo’s AZ-102 Microsoft Azure AI Engineer Associate Practice Exams.

These practice exams cover the relevant topics and question types that you can expect from the real exam. Each question has a detailed explanation and reference links, so you can understand why the correct answer is the most suitable solution. After you take the exams, you’ll be able to see which areas you need to improve on. Combining it with our cheat sheets, we’re confident that you’ll be able to pass the exam and have a deeper understanding of Azure.

Sample Practice Test Questions:

Question 1

You need to analyze customer satisfaction from e-commerce platforms by processing text data from surveys and reviews to determine sentiment and extract insights. The solution must leverage natural language processing (NLP) to classify the feedback effectively.

Which Azure AI service should you use?

1. Azure AI Language

2. Azure AI Content Safety

3. Azure AI Document Intelligence

4. Azure AI Speech

Question 2

You are using the Azure AI Custom Vision service to train an image classifier for a food retailer. The classifier will categorize images of products into categories such as fruits, vegetables, and beverages. After training the model, you need to evaluate its performance to ensure that the predictions are accurate.

Which two built-in metrics does Azure AI Custom Vision provide for the performance evaluation of the classifier? (Select TWO)

1. F1-Score
2. Precision

3. Recall
4. Confusion matrix
5. Precision-recall curve

For more Azure practice exam questions with detailed explanations, check out the Tutorials Dojo Portal:

Final Remarks

Success in the AI-102 exam requires theoretical understanding and practical experience with the Azure AI services. Focus your study efforts on the official Microsoft Learn materials and actively engage in hands-on exercises using the Azure portal, Studios, and SDKs. Practice exams are crucial for gauging your readiness and identifying areas that need further attention. Following this focused study path, you will be well-equipped to achieve the Microsoft Azure AI Engineer Associate certification. Good luck with your preparation!