AI-102: Azure AI Engineer Associate Practice Exams

Pass the Designing and Implementing a Microsoft Azure AI Solution (AI-102) certification exam on your first attempt with this comprehensive practice test suite. Containing 6 full-length, scenario-driven practice exams with 330 high-yield questions, this course gives you the knowledge, speed, and confidence needed to build, deploy, and monitor production AI applications using Azure AI Services, Azure OpenAI, Azure AI Search, and Cognitive APIs.

Each practice test mirrors the Pearson VUE examination interface, featuring 55 questions, an official 120-minute countdown timer, and a 70% passing threshold. Every question includes exhaustive itemized explanations for both the correct answers and the incorrect options, showing you precisely why an AI pipeline architecture works according to official Microsoft engineering standards.

Official Blueprint Domains Covered Across Every Practice Test:

1. Plan and Manage an Azure AI Solution (10-15% of Exam Score):

Create and manage Azure AI multi-service resources. Implement security controls including Microsoft Entra ID authentication, managed identities, API keys, and virtual network private endpoints. Monitor AI resource utilization and cost. Deploy Azure AI containers in disconnected on-premises or edge environments.

2. Implement Content Moderation Solutions (10-15% of Exam Score):

Implement Azure AI Content Safety to detect hate speech, violence, sexual content, and self-harm across text and image streams. Configure severity thresholds and custom blocklists.

3. Implement Computer Vision Solutions (15-20% of Exam Score):

Implement Azure AI Vision for image analysis, object detection, and image categorization. Build custom computer vision models with Custom Vision. Extract printed and handwritten text using Azure AI Document Intelligence (formerly Form Recognizer) prebuilt models (receipts, invoices, identity documents) and custom extraction models.

4. Implement Natural Language Processing Solutions (15-20% of Exam Score):

Implement Azure AI Language for text analytics including sentiment analysis, key phrase extraction, named entity recognition (NER), and personally identifiable information (PII) detection. Implement conversational language understanding (CLU) and Custom Question Answering. Implement Azure AI Speech speech-to-text, text-to-speech, and speech translation.

5. Implement Knowledge Mining Solutions (15-20% of Exam Score):

Architect enterprise search solutions with Azure AI Search (formerly Azure Cognitive Search). Configure data sources, indexers, skillsets, and search indexes. Implement vector search, hybrid search, and semantic ranking.

6. Implement Generative AI Solutions (15-20% of Exam Score):

Deploy and integrate Azure OpenAI models (GPT-4, text-embedding-ada-002). Implement Retrieval-Augmented Generation (RAG) pattern with enterprise data sources. Apply prompt engineering techniques, system messages, and few-shot examples.