AI is reshaping NetOps from scripted automation to intelligent, data driven workflows. We will show uses: incident triage, knowledge retrieval, traffic analysis, prediction, and contrast legacy monitoring with ML, NLP, and LLMs. See how RAG, text to SQL, and agent workflows enable real time insights across hybrid data. We will outline data pipelines and MLOps, address accuracy, reliability, cost, compliance, and weigh build vs buy. We will cover API integration and human in the loop guardrails.

In this hands-on lab, discover how to govern AI Apps & Agents using AI Gateway in Azure API Management. Learn to apply governance best practices by onboarding AI models, monitoring and controlling token usage, enforcing safety and compliance, and boosting performance with semantic caching. You’ll also govern MCP-based agent architectures by creating secure, efficient servers from APIs or connecting to backend MCP servers, equipping you to deliver responsible, resilient AI solutions at scale.

Build a smarter image classification app with Windows ML, now available generally available. This hands-on lab walks through dynamically downloading execution providers (EPs) for NPUs, compiling models for hardware-specific EPs, and running inference locally. Learn to deploy, debug, and optimize your app using WinML APIs. Ideal for developers exploring AI acceleration on Windows devices—no pre-distributed EPs required.

Looking to add on-device AI to your apps? Not sure how to get started? Join our lab to learn how to integrate local AI capabilities into your Windows apps using Windows AI APIs. Discover how to implement Semantic Search and Retrieval-Augmented Generation (RAG) to power intelligent information retrieval, and use Phi Silica for on-device text processing. This lab will walk you through key APIs, and best practices to build on-device AI solutions for Copilot+ PCs. Developers of all levels welcome.