Microsoft Certified: Azure AI Apps and Agents Developer Associate (AI-103)

AI pilots stall when developers lack a shared approach to building, grounding, and governing AI apps. Shadow projects then create security and compliance gaps. This AI-103 course gives your Azure development team a common foundation on Microsoft Foundry, from infrastructure and the Foundry SDK through agents, multimodal workloads, and governance.

Role fit: Azure developers and engineers who are comfortable with Python and work with architects, data scientists, or DevOps on AI projects. It is not an entry point. Pair newer staff with Azure AI Fundamentals (AI-900) or Azure Developer Associate (AZ-204) first.

Time investment: About 12 hours of video across 14 skills, with most skills running 48–63 minutes. Most learners can finish in a few weeks alongside project work.

Risk and compliance: The final skill covers securing, governing, and monitoring AI workloads. Earlier skills cover grounding and evaluating generation quality. Together, these help leaders set guardrails before AI features reach production.

Change management: Assign the course as a Playlist so the team moves through the same sequence. Use Team Reporting to track progress toward certification readiness.

IT teams complete this training so they can move AI projects from experiments to governed, production-ready apps and agents on Microsoft Foundry.

Typical scenarios include:

• Faster, consistent AI delivery: Developers automate AI infrastructure and build generative apps with the Foundry SDK, which reduces one-off builds and rework.
• More trustworthy answers: Teams build retrieval, grounding, and RAG pipelines. They extract content from documents and evaluate generation quality, so apps answer from company data rather than guesswork.
• Agents that can be operated: Engineers build agents in Foundry and orchestrate multi-agent workflows with observability. Issues can be traced instead of escalated blindly.
• Governed multimodal workloads: Teams add text, speech, image, and video capabilities with visual safety controls, then secure and monitor those workloads to support audit and risk reviews.

The result is standardized AI development capability across your team and less reliance on outside contractors for AI work.

Knowledge

• Microsoft Foundry platform foundations and how to design AI infrastructure
• Retrieval, grounding, and RAG patterns, including tool-augmented flows
• Methods for optimizing and evaluating generation quality
• Agent and multi-agent orchestration concepts, including observability
• Multimodal capabilities across text, speech, audio, image, and video, including visual safety
• Security, governance, and monitoring considerations for AI workloads

Ability

• Automate AI infrastructure and build generative apps with the Foundry SDK
• Build document and content extraction into retrieval pipelines
• Implement RAG and tool-augmented flows grounded in organizational data
• Build agents in Foundry and coordinate multi-agent workflows
• Add text analysis, speech, and image or video generation and editing to apps and agents
• Secure, govern, and monitor AI workloads, and prepare for the AI-103 exam