🧠 Microsoft Azure AI Engineer (AI-102)

An independent, free exam-preparation course that walks through the publicly published Microsoft AI-102 "Designing and Implementing a Microsoft Azure AI Solution" skills-measured outline. It covers planning and managing an Azure AI solution, selecting and securing Azure AI services, applying responsible AI, and building real solutions across computer vision (Azure AI Vision, Custom Vision, face and OCR), natural language processing (Azure AI Language — sentiment, entities, PII, translation), speech (speech-to-text and text-to-speech), document intelligence and content understanding, knowledge mining with Azure AI Search, generative AI with Azure OpenAI (prompt engineering, embeddings and RAG), and building agents — plus containers, deployment, monitoring and exam strategy. It uses visual lessons, worked examples, original self-check questions and a 45-question final exam. It is awareness/prep only — not an official Microsoft course or the AI-102 exam itself — and claims no Microsoft affiliation or endorsement. The course is organized into 22 modules, ending with a final exam (pass mark 80%). It is independent, free exam-preparation training — not an official or accredited review course.

What you'll learn

• AI-102 exam blueprint & the AI Engineer role
• Selecting the right Azure AI service
• Create, deploy & integrate Azure AI services
• Securing Azure AI services
• Responsible AI, content safety & moderation
• Image analysis with Azure AI Vision
• Custom Vision: classification & object detection
• Face detection & analysis
• OCR: extracting text from images
• Video analysis & spatial insights
• Text analytics with Azure AI Language
• Translation & custom translation models
• Speech-to-text & text-to-speech
• Custom speech, intent & keyword recognition
• Conversational language understanding & question answering
• Document Intelligence: prebuilt & custom models
• Content Understanding & multimodal extraction
• Knowledge mining with Azure AI Search
• Generative AI with Azure OpenAI
• Embeddings & RAG (grounding on your data)
• Building agents with Foundry Agent Service
• Containers, deployment, monitoring & exam strategy

Learning objectives

• Plan, create, deploy and secure Azure AI (Foundry) services and choose the right service for each workload
• Apply responsible AI principles, content safety, content filters, prompt shields and blocklists
• Build computer vision solutions with Azure AI Vision, Custom Vision, face detection and OCR
• Implement natural language processing with Azure AI Language — sentiment, key phrases, entities, PII and language detection
• Translate text and documents and build custom translation models
• Implement speech-to-text, text-to-speech, SSML and custom speech solutions
• Extract data from documents with Document Intelligence and Content Understanding
• Build knowledge-mining solutions with Azure AI Search, indexes, skillsets, semantic and vector search
• Build generative AI solutions with Azure OpenAI — prompt engineering, embeddings, RAG and agents
• Deploy with containers, monitor, manage cost and security, and apply an exam-day strategy
• Pass a 45-question exam (80% to earn your certificate)