
Learn the fundamentals of artificial intelligence and machine learning, and distinguish predictive ai from generative ai with azure-based use cases and large language model concepts.
Explore AI agents and compound AI systems, where an LLM uses APIs and external tools to autonomously plan and execute workflows, boosting ROI and automating business processes.
Explore core generative AI jargons like tokens, system prompts, user prompts, chat completions API, and multimodal versus unimodal models, highlighting how tokens drive costs and model behavior.
Discover Microsoft Foundry, an ai ecosystem platform as a service for building agentic ai at scale. Includes model catalog, agent service, Foundry IQ, and governance.
Learn to build an MCP-enabled Foundry agent that can search Microsoft Learn content and code samples, grounding responses in Microsoft docs and Azure AI resources.
Explore red-teaming to evaluate an AI agent with groundedness, retrieval, coherence evaluators, plus tool call accuracy. Build evaluations, generate attack queries for risk categories, and apply jailbreak and base64 strategies.
The Microsoft Azure AI Apps and Agents Developer Associate certification has evolved significantly with the introduction of Generative AI, agent-based architectures, Microsoft Foundry, and modern Azure AI services. This course has been fully updated to align with the latest AI-103 certification objectives, helping you stay current with Microsoft's rapidly evolving AI ecosystem while building real-world, production-ready AI solutions.
In this course, you'll learn how to design, build, and deploy end-to-end AI applications on Azure using services such as Azure OpenAI, Microsoft Foundry, Azure AI Search, Azure AI Content Understanding, and the Microsoft Agent Framework. You'll explore modern agentic AI architectures, Agent-to-Agent (A2A) communication, agent observability and tracing, orchestration workflows, and enterprise AI application design patterns.
Beyond Generative AI and agents, the course provides comprehensive coverage of Azure AI Language, Azure AI Vision, and Azure AI Document Intelligence services. You'll work with text analytics, custom classification, named entity recognition, question answering, image analysis, multimodal AI applications, and intelligent document processing solutions.
You'll also learn how to build Retrieval-Augmented Generation (RAG) solutions using Azure AI Search, implement low-code AI workflows using Microsoft Foundry, and understand the fundamentals of LLM fine-tuning and model customization. These skills are becoming increasingly important for modern Azure AI engineers and are reflected throughout the latest certification objectives.
Every module is designed to align with Microsoft's official AI-103 certification objectives while maintaining a strong focus on practical implementation. Rather than simply covering theory, you'll learn through hands-on demonstrations, real-world scenarios, and exam-focused explanations that help you both prepare for the certification exam and apply these skills in professional environments.
Whether your goal is to earn the AI-103 certification, advance your Azure AI engineering skills, or build modern enterprise AI and agent-based solutions, this course provides a structured, practical, and continuously updated learning path to help you succeed.