Microsoft Certified: Azure AI Engineer Associate Study Guide: Everything You Need to Know 2025
Your complete roadmap to passing the AI-102 certification exam. This comprehensive study guide covers all 5 exam domains with detailed explanations, study tips, and practice resources.
Quick Start
Essential steps to begin your preparation
Review Exam Objectives
View all domains →Take Assessment Quiz
Free practice test →Follow Study Plan
8-week roadmap →Full Practice Exams
Start practicing →Exam Domains & Objectives
Master these 5 domains to pass the AI-102 exam
Plan and Manage an Azure AI Solution
Implement Computer Vision Solutions
Implement Natural Language Processing Solutions
Implement Knowledge Mining and Document Intelligence Solutions
Implement Generative AI Solutions
8-Week Study Plan
Follow this structured plan to prepare for your Microsoft Certified: Azure AI Engineer Associate exam
Foundation
Understand core concepts and exam objectives
Focus Areas:
- Plan and Manage an Azure AI Solution
- Implement Computer Vision Solutions
Deep Dive
Master advanced topics and practical applications
Focus Areas:
- Implement Natural Language Processing Solutions
- Implement Knowledge Mining and Document Intelligence Solutions
Practice & Review
Take practice exams and review weak areas
Focus Areas:
- Implement Generative AI Solutions
Final Prep
Full practice exams and last-minute review
Focus Areas:
- Full-length practice tests
- Review all domains
Curated Study Resources
AI-curated resources with real links to help you prepare for the Microsoft Certified: Azure AI Engineer Associate exam
Complete Study Guide for Microsoft Certified: Azure AI Engineer Associate (AI-102)
The Azure AI Engineer Associate certification validates your ability to design, build, and deploy AI solutions using Azure AI services. This certification demonstrates expertise in computer vision, natural language processing, knowledge mining, document intelligence, and generative AI solutions. It's highly valued for professionals working with Azure's AI and machine learning ecosystem.
Who Should Take This Exam
- AI developers building solutions on Azure
- Data scientists implementing production AI systems
- Software engineers integrating AI services
- Solution architects designing AI-powered applications
- Machine learning engineers working with Azure
Prerequisites
- Strong understanding of Azure fundamentals (AZ-900 recommended)
- Experience with at least one programming language (Python or C# preferred)
- Basic knowledge of REST APIs and JSON
- Understanding of machine learning concepts
- Familiarity with Azure Portal and Azure CLI
- Experience with SDKs and development tools
Official Resources
AI-102 Official Exam Page
Official exam details, skills measured, and registration information
View ResourceAzure AI Engineer Associate Certification
Complete certification overview and learning paths
View ResourceAzure AI Services Documentation
Comprehensive documentation for all Azure AI services
View ResourceAzure OpenAI Service Documentation
Documentation for implementing generative AI solutions
View ResourceAzure Cognitive Search Documentation
Knowledge mining and search implementation guide
View ResourceAzure Computer Vision Documentation
Complete guide to implementing computer vision solutions
View ResourceAzure Language Service Documentation
Natural language processing implementation guide
View ResourceAzure Document Intelligence Documentation
Document analysis and form processing guide
View ResourceAzure AI Services SDK for Python
Python SDK reference for Azure AI services
View ResourceRecommended Courses
AI-102: Designing and Implementing a Microsoft Azure AI Solution
Microsoft Learn • 32 hours
View CourseMicrosoft Azure AI Engineer: Designing and Implementing an Azure AI Solution
Pluralsight • 20 hours
View CourseRecommended Books
Exam Ref AI-102 Designing and Implementing a Microsoft Azure AI Solution
by Daron Yondem
Official Microsoft exam reference guide covering all AI-102 objectives with practice questions
View on AmazonMicrosoft Azure AI Fundamentals: A Comprehensive Guide
by Jim Cheshire
Foundation book for understanding Azure AI services before tackling AI-102
View on AmazonAzure AI Engineer Associate Certification Study Guide
by Various Authors
Comprehensive study guide with hands-on exercises and practice exams
View on AmazonBuilding Intelligent Apps with Azure AI Services
by Tom Taulli
Practical guide to implementing AI solutions on Azure platform
View on AmazonPractice & Hands-On Resources
Official Microsoft Practice Assessment
Free official practice questions to assess readiness
View ResourceMeasureUp AI-102 Practice Tests
Premium practice exams with detailed explanations, most closely mirrors actual exam
View ResourceAzure AI Services Free Tier
Free tier access to practice with real Azure AI services
View ResourceMicrosoft Learn Sandbox Environment
Free temporary Azure environments for hands-on labs
View ResourceDocument Intelligence Studio
Interactive environment for document processing and form recognition
View ResourceAzure AI GitHub Samples
Official code samples and quickstarts for all AI services
View ResourceWhizlabs AI-102 Practice Tests
Additional practice exams with performance tracking
View ResourceCommunity & Forums
Microsoft Q&A for Azure AI
Official Microsoft community forum for Azure AI questions and discussions
Join Communityr/Azure Subreddit
Active community discussing Azure certifications, including AI-102 study tips and experiences
Join Communityr/AzureCertification Subreddit
Dedicated subreddit for Azure certification preparation and exam experiences
Join CommunityAzure AI Services Tech Community
Official Microsoft Tech Community for AI services discussions and updates
Join CommunityMicrosoft Learn Discord
Official Microsoft Learn community Discord with certification study channels
Join CommunityJohn Savill's YouTube Channel
Excellent Azure deep-dive videos and certification study sessions
Join CommunityStudy Tips
Hands-On Practice Strategy
- Create an Azure free account immediately and practice with real services - theoretical knowledge alone is insufficient
- Use all the Studio environments (Vision, Language, Speech, OpenAI, Document Intelligence) extensively before the exam
- Build at least 3-4 complete projects integrating multiple AI services to understand real-world scenarios
- Practice with both Python and REST API implementations as the exam covers both approaches
- Keep a lab journal documenting configuration steps, common errors, and solutions
SDK and API Mastery
- Memorize key SDK class names and methods - the exam tests specific implementation knowledge
- Understand the differences between v3.0, v3.1, and newer API versions for various services
- Practice authentication methods: subscription keys, managed identities, and Azure AD integration
- Know REST API endpoint patterns and how to construct proper request URLs
- Understand asynchronous operations and polling patterns for long-running operations
Domain-Specific Focus Areas
- NLP is 30% of the exam - spend proportional time here mastering CLU, QnA Maker successor, and custom text analytics
- Generative AI (20%) requires understanding prompt engineering, token limits, embeddings, and RAG patterns
- For Computer Vision, understand when to use each service: Computer Vision vs Custom Vision vs Face API
- Knowledge Mining requires deep understanding of AI enrichment pipeline, skillsets, and custom skills
- Security and monitoring appear across all domains - know managed identities, private endpoints, and Azure Monitor integration
Service Configuration and Optimization
- Understand pricing tiers (F0/Free, S0/Standard, S1-S4) and what features are available in each
- Know scaling options, rate limits, and quota management for production scenarios
- Study container deployment options for all AI services that support it
- Understand regional availability and data residency considerations
- Master content filtering, responsible AI features, and compliance requirements
Exam Question Patterns
- Case studies require reading multiple screens - take notes on requirements before answering questions
- Many questions test choosing the BEST solution when multiple options could work
- Code-based questions often focus on authentication, endpoint configuration, and key parameters
- Scenario questions frequently involve troubleshooting - know common error codes and solutions
- Some questions have multiple correct answers - read carefully whether to select 'all that apply' or 'single best answer'
Key Documentation to Bookmark
- Bookmark quickstart pages for each service - they contain essential code patterns
- Save the AI services REST API reference pages for quick lookup during practice
- Keep the pricing calculator page handy to understand cost optimization scenarios
- Bookmark the 'What's new' pages for each service to understand latest features
- Save comparison pages (like OCR vs Read API, LUIS vs CLU) for decision-making scenarios
Practical Lab Exercises
- Complete every Microsoft Learn module lab - they're designed to match exam scenarios
- Replicate exam scenarios: build a custom vision model, create a search index, deploy OpenAI chat
- Practice monitoring solutions with Application Insights and Azure Monitor
- Implement security best practices: use Key Vault, configure private endpoints, set up managed identities
- Time your lab work - understand how long real implementations take
Migration and Version Awareness
- Understand LUIS to CLU migration path - exam may test both
- Know QnA Maker to Question Answering migration within Language Service
- Be aware of Form Recognizer rebranding to Document Intelligence
- Understand Cognitive Services consolidation into Azure AI Services
- Know which features are preview vs generally available
Exam Day Tips
- 1Arrive 15 minutes early for online exams to complete check-in process
- 2Have a government-issued ID ready that exactly matches your Microsoft certification profile
- 3Clear your desk completely for online proctored exams - only water in clear container allowed
- 4Read each question carefully - many test choosing the 'best' or 'most cost-effective' solution
- 5Flag difficult questions and return to them later - don't get stuck on one question
- 6For case study questions, take notes on requirements before viewing the questions
- 7Watch for keywords like 'minimum administrative effort', 'most secure', 'lowest cost'
- 8Lab questions cannot be reviewed later - complete them carefully before moving on
- 9Budget approximately 2 minutes per question to allow review time
- 10If unsure between two answers, consider the context: is it about security, cost, or performance?
- 11Remember that some questions intentionally include more information than needed - focus on the actual requirement
- 12Use the calculator and notepad features provided in the exam interface
- 13Don't panic if you see unfamiliar service names - use logical reasoning based on related services you know
- 14Trust your hands-on experience - practical knowledge often reveals the correct answer
- 15Submit your exam only after reviewing all flagged questions and using available time
Study guide generated on January 8, 2026
Pro Study Tips
Expert advice to maximize your study effectiveness
Active Learning Strategies
- Hands-on practice: Apply concepts in real scenarios
- Teach others: Explain concepts to reinforce learning
- Take notes: Write summaries in your own words
Exam Day Preparation
- Get enough sleep: Rest well the night before
- Review key points: Go through your notes and cheat sheets
- Time management: Practice pacing with timed exams
Continue Your Preparation
More resources to help you succeed
Complete Microsoft Certified: Azure AI Engineer Associate Study Guide
This comprehensive study guide will help you prepare for the AI-102 certification exam offered by Microsoft Azure. Whether you are a beginner or experienced professional, this guide covers everything you need to know to pass on your first attempt.
What You Will Learn
Our study guide covers all 5 exam domains in detail:
- Plan and Manage an Azure AI Solution (15%)
- Implement Computer Vision Solutions (20%)
- Implement Natural Language Processing Solutions (30%)
- Implement Knowledge Mining and Document Intelligence Solutions (15%)
- Implement Generative AI Solutions (20%)
Recommended Timeline
Most candidates need 6-8 weeks of dedicated study to pass the Microsoft Certified: Azure AI Engineer Associate exam. We recommend studying 1-2 hours daily and taking practice exams weekly to track your progress.
Next Step: Start with our free practice test to assess your current knowledge level.