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Azure AI App and Agent Developer
Course Description
AI-103: Developing Azure AI Apps and Agents
Build production-ready generative AI apps and intelligent agents with Microsoft Foundry. This hands-on Azure AI course takes software developers from first model deployment to secure, multi-agent solutions. It suits beginners and experienced engineers alike, and it prepares you for the AI-103 exam.
Duration: 5 days (35-40 hrs) | Format: Instructor-led or self-paced | Level: Beginner to advanced | Prerequisites: Basic Python or C# and REST APIs
What You’ll Learn
- Build generative AI apps with Microsoft Foundry, RAG pipelines, and prompt optimization
- Create AI agents with tools, memory, and Model Context Protocol (MCP)
- Orchestrate multi-agent workflows with the Microsoft Agent Framework
- Process images, video, speech, and documents with multimodal AI
- Extract and ground knowledge with Azure AI Search, Content Understanding, and Document Intelligence
- Apply responsible AI safeguards and deploy with monitoring
Who Is This Course For?
Software developers, cloud engineers, and solution architects building AI on Azure. Beginners get an on-ramp module and guided labs. Experienced engineers can skip ahead to advanced content.
Course Curriculum
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Course Eligibility
Audience profile
This course is intended for software developers wanting to build AI infused applications that leverage Microsoft Foundry. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement knowledge connections or tools in your agentic applications. This course also covers multimodal capabilities and understanding of complex content. This course was designed for software engineers concerned with building, managing and deploying AI solutions that leverage Microsoft Foundry. They are familiar with Python and have knowledge on using APIs and SDKs to build agents and generative AI solutions on Azure.
Audience prerequisites
Before attending this course, students should have: familiarity with Python programming; experience using REST APIs and SDKs to build cloud-connected applications; foundational knowledge of Azure services and the Azure portal; and an understanding of basic AI/ML concepts such as machine learning models and inferencing. Prior experience with Azure AI services is helpful but not required.
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