Microsoft Certified: Azure AI Apps and Agents Developer Associate

Published weight 25-30%. Choosing appropriate Microsoft Foundry services and models for generative AI and agents, setting up AI solutions in Foundry (infrastructure, deployment, CI/CD), managing/monitoring/securing AI systems, and implementing responsible AI across generative and agentic systems.

• Choose the appropriate Foundry services and models for generative AI and agents
• Set up AI solutions in Foundry (infrastructure, deployment, CI/CD)
• Manage, monitor, and secure AI systems
• Implement responsible AI across generative AI and agentic systems

Published weight 30-35%. Building generative applications with Foundry (LLMs, RAG, tool-augmented flows, evaluation, SDKs), building agents (roles, tools, function-calling, memory, multi-agent orchestration, approval flows), and optimizing/operationalizing generative AI systems.

• Build generative applications by using Foundry (LLMs, RAG, tool flows, evaluation, SDKs)
• Build agents by using Foundry (roles, tools, function-calling, memory, multi-agent, approvals)
• Optimize and operationalize generative AI systems (prompt tuning, observability, orchestration)

Published weight 10-15%. Image- and video-generation solutions, multimodal understanding workflows (captioning, visual Q&A, Content Understanding), and responsible AI for multimodal content (unsafe-content filters, indirect prompt-injection mitigation, visual policy).

• Design and implement image- and video-generation solutions
• Design and implement multimodal understanding workflows
• Implement responsible AI for multimodal content

Published weight 10-15%. Language-model text analysis (entities, summaries, structured JSON, sentiment, translation, domain customization) and speech solutions (speech-to-text/text-to-speech, speech as an agent modality, speech translation).

• Apply language model text analysis (extraction, sentiment, translation, customization)
• Implement speech solutions (STT/TTS, speech as an agent modality, translation)

Published weight 10-15%. Retrieval and grounding pipelines (ingest/index, semantic/hybrid/vector search, enrichment, RAG ingestion, OCR) and extracting content from documents with multimodal pipelines and Content Understanding.

• Build retrieval and grounding pipelines (indexing, hybrid/vector search, RAG, OCR)
• Extract content from documents (OCR, layout, field extraction, Content Understanding)