AI-103 Developing AI Apps and Agents on Azure: The Decision Making Method

AI-103 Developing AI Apps and Agents on Azure The Decision-Making Method Master Microsoft Foundry. Build AI Applications. Pass the AI-103 Exam. Updated for the latest AI-103 certification objectives The AI-103 certification marks a major evolution in Microsoft's AI certification path. As the successor to AI-102, AI-103 is a code-first Associate certification focused on developing, deploying, securing, and operationalizing AI applications and AI agents using Microsoft Foundry. Unlike AI-901, which emphasizes AI concepts, AI-103 evaluates your ability to make implementation decisions, interpret Python SDK examples, and select the right architecture for real-world scenarios. Passing this exam requires more than knowing Azure AI services. You must understand why one solution is better than another. That's why this guide follows The Decision-Making Method. Instead of memorizing services, you'll learn how experienced AI developers identify constraints and choose the right Microsoft Foundry capability for each scenario. Inside you'll master ? Microsoft Foundry ? Azure AI Foundry SDK ? AI Agents ? Prompt Engineering ? RAG and Fine-Tuning ? Azure AI Search ? Retrieval Design ? Tool & Function Calling ? Multi-Agent Architectures ? Model Evaluation ? Responsible AI & Content Safety ? Computer Vision ? Language & Speech Services ? Information Extraction ? Document Intelligence ? Managed Identity & Microsoft Entra ID ? Deployment and Operationalization ? Decision tables for every exam objective ? Hands-on decision labs ? Python SDK read-along examples ? Full-length practice exam with detailed explanations Built for the latest AI-103 exam This guide covers all five official AI-103 domains, with special emphasis on Generative AI and Agentic Solutions, the largest and most heavily weighted section of the certification. Rather than memorizing services, you'll learn to answer questions such as: When should I use Prompt Engineering, RAG, or Fine-Tuning? How should I design an AI Agent? When is a multi-agent architecture appropriate? Which authentication model is most secure? Which evaluation strategy best fits the scenario? These are the implementation decisions the AI-103 exam is designed to test. Why this book is different Every chapter includes: Decision tables Architecture comparison frameworks Foundry SDK examples Hands-on labs Exam Tips Key Takeaways Associate-level review questions Detailed answer explanations You'll learn not only what to implement, but why one architectural decision is better than another. Who should read this book? Ideal for: AI-103 candidates Azure AI Engineers Microsoft Foundry developers Cloud Architects AI Engineers moving from AWS or Google Cloud AI-901 knowledge is helpful but not required. Part of the Azure Certification Decision Guides Series Learn Microsoft certifications through decision-making rather than memorization. Every guide combines decision tables, comparison frameworks, architectural thinking, and realistic practice questions to help you understand why an answer is correct—not simply what to memorize. Master the decisions behind the certification—not just the exam objectives.