Azure AI and Machine Learning in the Agentic Era
A Practitioner’s Guide to Building Production Systems
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Beschreibung
Most enterprise AI projects succeed as pilots and fail at scale. The difference is almost always the system, not the model.
Embark on a journey through the full Azure AI ecosystem, from the early days of Azure Machine Learning to the intelligence of Microsoft Foundry, bridging classical ML, multi-modal AI services, and next-generation generative and agentic systems. Design data foundations, choose and deploy models, orchestrate RAG and multi-agent workflows over MCP, operationalize and govern the whole stack with Responsible AI for real-world systems. Explore the seven-layer architecture that underpins production AI systems: Foundation, Knowledge, Intelligence, Orchestration, Experience, Observability, and Trust, and use it to build hybrid ML-GenAI applications, enterprise agents, and Autopilots. By the end of the book, readers will not only understand the mechanics of Azure’s AI ecosystem, but also the philosophy behind building intelligent, explainable, secure, and sustainable AI for the Agentic Era.
In today’s rapidly evolving AI landscape, organizations face the critical challenge of implementing AI solutions that are both powerful and practical. This book bridges the gap between Azure’s vast AI capabilities and real-world business needs, making it essential for professionals who need to deliver results — not just understand concepts. The combination of comprehensive coverage, hands-on implementation guidance, and strategic architectural frameworks makes it indispensable for anyone responsible for Azure AI initiatives.
This is not a survey of Azure services. It is a guide to building systems that work.
What You Will Learn:
- Master Azure’s complete AI ecosystem, from machine learning and pre-built AI services to Azure OpenAI, MAI models, and Microsoft Foundry
- Go beyond theory with hands-on Azure exercises, production deployment strategies, reference architectures, and real case studies
- Build, deploy, and operate AI solutions that span predictive models, generative applications, RAG systems, and enterprise agents
- Peek into the world of Agents, multi-agent frameworks, MCP, and quantum ML
Who This Book is For:
This book is designed for data scientists, AI/ML engineers, solution architects, and platform engineers who want to build end-to-end AI and Machine Learning systems on Azure. It is equally useful for tech leads and engineering managers shaping enterprise AI strategy in the Agentic Era.
A practical blueprint to building production-ready AI systems spanning data, models, agents, operations, and governance Master the modern AI stack, from machine learning and foundation models to RAG, agents, MCP, and Microsoft Foundry Accelerate enterprise AI adoption with Azure reference architectures, deployment patterns, and real-world case studies
Autor*in
Urvi Sengar
Themen in »Azure AI and Machine Learning in the Agentic Era«
Azure Machine Learning Azure AI Foundry Generative AI Azure RAG Enterprise AI Implementation Azure Cognitive Services Multi-agent AI Systems Agentic AI Agents Responsible AI Practices ML to GenAI Migration Azure AI Production Hybrid AI and Machine Learning Architecture Model Context Protocol