Question 1 of 20 Domain
0%

Exam Complete!

You answered 0 out of 20 questions correctly

Ready for the Complete Exam?

Get access to all 1,020 practice questions with detailed explanations

About the Azure AI-102 Exam

The Microsoft Certified: Azure AI Engineer Associate (AI-102) exam validates your expertise in designing, building, and deploying AI solutions using Azure AI services. This associate-level certification is designed for AI engineers, machine learning engineers, and developers who integrate AI capabilities into applications using Azure's pre-built AI services. Released in its current form in 2024, the AI-102 emphasizes modern AI technologies including Azure OpenAI Service, Computer Vision, Language Understanding, and Document Intelligence.

The exam consists of 40-60 questions to be completed in 100 minutes. Questions include multiple-choice, case studies, and scenario-based questions that test your ability to design AI workflows, select appropriate AI services, and implement responsible AI practices. A passing score of 700/1000 is required. The exam costs $165 USD and assumes you have experience with Python or C# and understand REST APIs and SDKs.

Exam Domains and Weighting:

  • Plan and Manage an Azure AI Solution (15-20%) - Selecting AI services, provisioning resources, managing Azure AI services, implementing security (managed identities, Key Vault), and monitoring AI solutions.
  • Implement Image and Video Processing Solutions (20-25%) - Computer Vision API, Custom Vision for image classification and object detection, Face API for face detection and recognition, and video analysis with Video Indexer.
  • Implement Natural Language Processing Solutions (20-25%) - Language Service (entity recognition, sentiment analysis, key phrase extraction), Translator Service, Speech Service (speech-to-text, text-to-speech), and conversational AI with Language Understanding (LUIS) and Azure Bot Service.
  • Implement Knowledge Mining and Document Intelligence Solutions (15-20%) - Azure AI Search (formerly Cognitive Search) with custom skillsets, Document Intelligence (formerly Form Recognizer) for form processing and custom models.
  • Implement Generative AI Solutions (10-15%) - Azure OpenAI Service integration, prompt engineering, GPT models, DALL-E for image generation, content filtering, and responsible AI implementation.

This certification is valid for one year from the date of completion. To maintain your certification status, you must pass a renewal assessment before the expiration date. The AI-102 is ideal for developers with 6-12 months of Azure experience who want to specialize in AI solution development using pre-built cognitive services rather than building models from scratch.

Why Take This Certification?

  • High Demand in AI Development: Azure AI Engineers earn average salaries of $125,000-$140,000 annually (Source: AI Engineering Salary Reports 2025), with senior AI engineers exceeding $150,000-$175,000. The integration of Azure OpenAI Service (including GPT-4 and DALL-E) into enterprise applications has made this certification particularly valuable, with demand growing 25% year-over-year.
  • Practical AI Skills Without ML Expertise: Unlike data science certifications (DP-100), AI-102 focuses on integrating pre-built AI services into applications. You don't need deep machine learning knowledge—just the ability to call APIs, configure services, and implement AI workflows. This makes AI capabilities accessible to application developers.
  • Cutting-Edge Generative AI Experience: The AI-102 is one of the few certifications that covers Azure OpenAI Service integration, prompt engineering, and responsible AI practices. Over 60% of Fortune 500 companies are implementing generative AI in 2025, creating strong demand for certified professionals who can deploy these solutions securely.
  • Foundation for AI Career Path: The AI-102 serves as a stepping stone to advanced Azure certifications and specialized AI roles. It demonstrates your ability to build intelligent applications with computer vision, natural language processing, document intelligence, and conversational AI—skills applicable across industries from healthcare to finance.

What You'll Learn in the AI-102 Exam

The AI-102 exam covers a comprehensive range of Azure AI services and implementation patterns for building intelligent applications. You'll demonstrate expertise in integrating pre-built AI capabilities, configuring AI workflows, and implementing responsible AI practices across computer vision, natural language processing, and generative AI scenarios.

Core Azure AI Services

  • Generative AI: Azure OpenAI Service integration, GPT-3.5/GPT-4 models, prompt engineering techniques, embeddings, DALL-E image generation, content filtering, and responsible AI configurations.
  • Computer Vision: Computer Vision API (OCR, image analysis, spatial analysis), Custom Vision (image classification, object detection, custom models), Face API (detection, recognition, verification), and Video Indexer.
  • Natural Language Processing: Language Service (named entity recognition, sentiment analysis, key phrase extraction, language detection), Translator (real-time translation), and Question Answering service.
  • Speech Services: Speech-to-text, text-to-speech, speech translation, custom speech models, and speaker recognition.
  • Conversational AI: Language Understanding (LUIS) for intent recognition, Azure Bot Service integration, and multi-turn conversations.
  • Knowledge Mining: Azure AI Search (formerly Cognitive Search) with built-in skills, custom skillsets, enrichment pipelines, and semantic search capabilities.
  • Document Intelligence: Form Recognizer for prebuilt models (invoices, receipts, IDs), custom form processing, and document analysis.

Key AI Implementation Patterns

  • Designing AI solution architectures with appropriate service selection for specific use cases.
  • Implementing security for AI services using managed identities, Azure Key Vault, and network restrictions.
  • Configuring containers for offline deployment of AI services (speech, language, vision).
  • Creating custom models with Custom Vision, Form Recognizer, and conversational language understanding.
  • Implementing responsible AI practices including content filtering, bias detection, and explainability.
  • Monitoring AI solution performance, costs, and usage with Application Insights and Azure Monitor.

How to Prepare for the AI-102 Exam

The AI-102 requires hands-on experience with Azure AI services and programming skills in either Python or C#. While no formal prerequisites exist, Microsoft recommends familiarity with Azure fundamentals (AZ-900 level knowledge) and basic programming concepts. Most candidates need 6-8 weeks of focused preparation combining theoretical study with extensive hands-on practice.

  1. Review Azure AI Services Documentation (1-2 weeks): Study the official Microsoft AI-102 exam page and download the skills outline. Focus on understanding when to use each AI service—Computer Vision vs Custom Vision, Language Service vs LUIS, etc. Review the Azure AI Services documentation for service capabilities and limitations.
  2. Hands-On Labs with Azure AI Services (3-4 weeks): Create a free Azure account and practice with each AI service using the SDKs (Python or C#). Build sample projects: image classification with Custom Vision, sentiment analysis with Language Service, chatbot with LUIS and Bot Service, and document processing with Form Recognizer. Critically, practice with Azure OpenAI Service including prompt engineering and content filtering configurations.
  3. Learn Service Configuration and Security (1 week): Practice provisioning AI services via Azure Portal and ARM templates. Implement managed identities for secure service access, store API keys in Key Vault, configure virtual networks and private endpoints, and set up monitoring with Application Insights. Understand pricing tiers and when to use containerized AI services for offline scenarios.
  4. Practice Exams and Scenario Analysis (1-2 weeks): Take timed practice tests focusing on scenario-based questions where you must select the appropriate AI service for a business requirement. Review case studies that test your ability to design end-to-end AI solutions. Identify weak areas and revisit documentation—commonly challenging topics include Azure AI Search enrichment pipelines and responsible AI implementation.

Leverage Microsoft Learn's free AI-102 learning paths, practice with GitHub code samples, and join Azure AI communities. Remember that the exam heavily emphasizes Azure OpenAI Service (10-15% weight) and practical implementation over theoretical AI concepts, so prioritize hands-on coding practice.

Frequently Asked Questions

No. All Nex Arc practice questions are original content created by certified professionals based on official exam guides and publicly available documentation. We do not offer brain dumps, leaked questions, or actual exam content. Using or distributing real exam questions violates certification provider agreements and can result in certification revocation. Our questions are designed to test the same knowledge and skills as the real exam, using different scenarios and wording.
The Azure AI-102 exam consists of 40-60 questions that you need to complete in 100 minutes. Questions include multiple-choice, case studies, and scenario-based questions related to Azure AI solutions. Our premium course includes 1,020 practice questions across 17 full practice exams with detailed explanations.
The passing score is 700 out of 1000. Azure uses a scaled scoring model, and not all questions carry the same weight. Focus on understanding cloud fundamentals rather than memorizing answers.
Click on the "Buy Now" button in the sidebar to purchase the complete course. After payment, you'll have instant access to all 17 practice exams with 1,020 questions with detailed explanations and lifetime access.
Yes, you need proficiency in either Python or C# to pass the AI-102 exam. The exam tests your ability to write code using Azure AI SDKs, configure services programmatically, and integrate AI capabilities into applications. You should be comfortable with REST APIs, JSON, and asynchronous programming. However, you don't need deep machine learning or data science knowledge—the focus is on using pre-built AI services, not building models from scratch.
The AI-102 certification is valid for one year from the date you pass the exam. To maintain your certified status, you must complete a free renewal assessment on Microsoft Learn before your certification expires. The renewal assessment focuses on new features and updates to Azure AI services released during your certification year, particularly updates to Azure OpenAI Service and other rapidly evolving AI capabilities.
The AI-102 exam costs $165 USD. If you don't pass on your first attempt, you must wait 24 hours before retaking the exam. After a second failed attempt, you must wait at least 14 days before each subsequent retake. Microsoft offers discounts for students, educators, and participants in Microsoft Learn Cloud Skills Challenges.
Image and Video Processing (20-25%) and Natural Language Processing (20-25%) carry the highest weight. Within these domains, expect questions on Computer Vision API, Custom Vision model training, Language Service configuration, speech services, and conversational AI. Generative AI (10-15%) is a growing focus area—practice extensively with Azure OpenAI Service, prompt engineering, and content filtering. Knowledge mining with Azure AI Search is also frequently tested.
AI-102 focuses on integrating pre-built AI services into applications using SDKs and APIs, while DP-100 focuses on building, training, and deploying custom machine learning models using Azure Machine Learning. AI-102 is ideal for developers who want to add AI capabilities (vision, language, search) to applications without deep ML expertise. DP-100 is for data scientists who design and train custom models from scratch. Choose AI-102 if you're an application developer; choose DP-100 if you're pursuing a data science career.
Loading...