Microsoft - Developing AI Apps & Agents on Azure (Exam AI-103)

Colleagues, the “Microsoft - Developing AI Apps and Agents on Azure (Exam AI-103)” credential is the successor to the beloved AI-102 (Azure AI Engineer Associate), and it represents a quantum leap in scope and ambition. Where the AI-102 focused on consuming individual Azure AI Services--a bit of vision here, some NLP there--the AI-103 is built around Microsoft Foundry as the unified platform for building, deploying, and operating AI applications and autonomous agents. The exam demands that you plan Azure infrastructure for AI, implement RAG pipelines, build multi-agent orchestrations with safeguards, and operationalize the whole stack with tracing, token analytics, and safety monitoring. Learn How To: Choose the right model for each task--LLMs, small language models, multimodal models, and Foundry Tools. Design Azure infrastructure for AI apps and agent-based solutions with proper security and CI/CD integration. Configure safety filters, guardrails, risk detection, and content moderation for responsible AI. Deploy and consume models via Foundry, implementing RAG with semantic, hybrid, and vector search. Build agents with retrieval, function-calling, conversation memory, and multi-agent orchestration. Implement model reflection, chain-of-thought evaluations, and self-critique loops. Build image and video generation solutions with editing workflows including inpainting and mask-based edits. Implement speech-to-agent interactions with custom speech models and multimodal audio reasoning. Build retrieval and grounding pipelines with content ingestion, indexing, and enrichment. Extract structured information from documents using multimodal pipelines combining OCR, layout analysis, and field extraction. Skill-based training modules include: 1) Choose Foundry Services, Models, and Integration Approach, 2) Set Up AI Solutions in Foundry, 3) Manage and Monitor AI Systems, 4) Secure AI Systems with Zero Trust, 5) Identity and Networking, 6) Implement Responsible AI Across Generative and Agentic Systems, 7) Prompt Engineering and Optimizing Generation Behavior, 8) Implement Retrieval-Augmented Generation and Multistep Reasoning Workflows, 9) Evaluate, Observe, and Operationalize Generative AI Apps, 10) Build Agents with Foundry: Roles, Memory, Tools, and Function, 11) Orchestrate Multi-Agent Solutions and Monitor Agent Behavior, 12) Generate and Edit Images and Videos with Foundry, 13) Multimodal Understanding and Visual Analysis Workflows, 14) Implement Responsible AI for Multimodal Content, 15) Apply Language Model Text Analysis and Translation, 16) Implement Speech Solutions for Agentic Interactions, 16) Build Retrieval and Grounding Pipelines, and 17) Extract Content from Documents with Content Understanding.

Enroll today (teams & executives are welcome): https://tinyurl.com/4ynsxkc7 

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle)

Much career success, AI Academy (please subscribe and share with your team)