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AI-102Free Study Guide

Microsoft Azure AI Engineer Associate AI-102The Complete Beginner's Guide

This guide covers all official exam objectives for the AI-102 certification, including planning, managing, and implementing Azure AI solutions across NLP, computer vision, generative AI, knowledge mining, and agentic AI.

16 chapters
~3 hours total read
Free — no signup required
By Johnson Ajibi · Senior Network & Security Engineer · MSc IT Security

How to use this guide

This guide works best as a loop: read a chapter, test yourself with practice questions, look up unfamiliar terms in the glossary, then move to the next chapter.

① Read a chapter② Answer practice questions③ Review missed answers④ Repeat
Study Chapters

16 chapters covering every exam objective. Each chapter includes key concepts, exam tips, common traps, comparison tables, and a 5-question quiz at the end.

Start Chapter 1
Practice Questions

Free timed and untimed practice with instant feedback and full explanations. Pick 10–120 questions per session. Filter by domain to drill your weak areas.

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Glossary

Every AI-102term defined and searchable. Use it when a chapter mentions a concept you haven't seen before or want a quick refresher on.

Browse glossary
Exam Overview

Exam blueprint, domain weights, passing score, duration, cost, and registration links. Start here if you're new to this certification.

View exam guide

Chapters — AI-102

1

Azure AI Fundamentals and Solution Planning

Objective 1.1 · Analyze solution requirements and plan an AI solution

12m
2

Managing Azure AI Resources and Security

Objective 1.2 · Manage Azure AI resources, security, and governance

12m
3

Responsible and Ethical AI on Azure

Objective 1.3 · Implement responsible AI principles and governance

12m
4

NLP Solution Planning and Text Processing with Azure AI Language

Objective 2.1 · Plan and implement NLP solutions using Azure AI Language

12m
5

Question Answering and Conversational Language Understanding

Objective 2.2 · Implement question answering and conversational language understanding solutions

12m
6

Translation and Speech Services

Objective 2.3 · Implement translation and speech solutions

12m
7

Computer Vision: Image Analysis and Classification

Objective 3.1 · Implement image analysis and classification solutions

12m
8

Computer Vision: Object Detection, OCR, and Face Services

Objective 3.2 · Implement object detection, OCR, and facial recognition solutions

12m
9

Computer Vision: Video Analysis and Custom Vision

Objective 3.3 · Implement video analysis and custom vision solutions

12m
10

Generative AI: Model Selection and Deployment on Azure

Objective 4.1 · Plan, select, and deploy generative AI models

12m
11

Generative AI: Prompt Engineering and Retrieval-Augmented Generation

Objective 4.2 · Implement prompt engineering and RAG patterns

12m
12

Generative AI: Responsible Use, Fine-Tuning, and Customization

Objective 4.3 · Implement responsible use, fine-tuning, and customization of generative AI models

12m
13

Knowledge Mining with Azure Cognitive Search

Objective 5.1 · Implement knowledge mining solutions using Azure Cognitive Search

12m
14

Knowledge Mining with Azure Document Intelligence

Objective 5.2 · Implement knowledge mining solutions using Azure Document Intelligence (Form Recognizer)

12m
15

Agentic AI and Agent-Based Solutions

Objective 6.1 · Plan and implement agentic AI solutions

12m
16

Agentic Solutions: Orchestration and Tool Integration

Objective 6.2 · Implement agent orchestration and tool calling

12m

Ready to test your knowledge?

Free AI-102 practice questions with full explanations. Test what you learn chapter by chapter.

AI-102 Practice Questions