End‑to‑End Machine Learning with Microsoft Fabric: AI‑Powered Workflows in Action
Take a hands-on, scenario-driven tour of the complete machine learning lifecycle—fully within Microsoft Fabric and accelerated by built-in AI tools.
This workshop begins with data ingestion using Copilot‑assisted pipelines and AI Functions, followed by feature engineering in guided notebooks. You’ll build and optimize both AutoML and custom models, register and deploy them using Fabric’s MLOps features, and analyze experiment results directly inside the platform. The session wraps with inferencing scenarios, including ad‑hoc inferencing in Power BI, batch inferencing in automated pipelines, and deploying a Data Agent for on‑demand product Q&A—all within a single Fabric environment.
This workshop is ideal for data professionals and ML practitioners seeking practical, hands‑on experience with end‑to‑end machine learning. Attendees will learn how to leverage AI-powered tools to simplify complex tasks like feature engineering, model optimization, and deployment, while integrating ML outputs into business intelligence tools and automated workflows—accelerating AI projects and enabling smarter decision-making all within Fabric.
Main Topics Covered:
Data Science
Technical Level:
200 – Intermediate; 300 – Advanced
Who Should Attend:
Data Engineers, Data Analysts, Business Analysts, Business Decision Makers, Data Citizens
Prerequisites:
Basic SQL and Python or R skills, understanding of lakehouses and warehouses, access to a Fabric tenant or capacity.
Microsoft Accreditation:
None
Features Covered:
Pipelines, Lakehouse, Notebooks, Power BI Reports, Semantic Model, ML Model
See you there for a day of learning, networking, and all things Fabric-tastic! 🌐✨
Maria Mohr
Maria Mohr completed her PhD in Mathematical Statistics at the University of Hamburg before joining Obungi in 2019. As Data & AI Engineer and Technical Architect she built up deep expertise on the data platform portfolio in the Microsoft Azure Cloud and Microsoft Fabric and was part of the Fabric private preview team six months before its launch. With her knowledge and experience, she supports customers in conceptualizing data strategies and implementing data analytics and AI solutions in the Microsoft ecosystem.
Jannik Luxenburger
Jannik Luxenburger joined Obungi in 2018 after getting his Master’s Degree in Advanced Computational Biology at Universität des Saarlandes. In various roles as software engineer, IT project manager and Data & AI Solution Architect he built deep knowledge on Azure cloud architectures, AI data platforms and IT projects in general. In recent years the focus of his work has shifted towards designing data platform and AI solutions using Microsoft Fabric, Azure Databricks and many other Azure Services. After being part of the Microsoft Fabric private preview for 6 months before launch, he assisted many customers in their transition to Microsoft Fabric and in the realization of enterprise-level generative AI use-cases.
