This course covers how to prepare, enrich, and serve data for analysis by consumers such as data analysts, report developers, and AI agents. The course focuses on designing dimensional models and transforming data by using dataflows, notebooks, and T-SQL across lakehouses, warehouses, and eventhouses in Microsoft Fabric. The course also covers building and optimizing semantic models, managing the analytics development lifecycle, and enforcing security and governance across data assets.

• Source streaming data sources into Microsoft Fabric.
• Use real time Eventstream in Microsoft Fabric.
• Query data in a KQL database in Microsoft Fabric.
• Create real time dashboards in Microsoft Fabric.

This course is designed to build practical skills in implementing data science and machine learning solutions using Microsoft Fabric. The course explores the complete end-to-end data science process, from understanding and exploring data to preparing and transforming datasets for analysis. Students will learn how to train, evaluate, and track machine learning models, as well as how to deploy those models and generate predictions using Microsoft Fabric tools and capabilities.

This course is designed as an introduction to Power BI for data analysis and reporting. Skills include connecting to data and basic data preparation tasks using Power Query, designing report pages for optimal user experience, and exploring how Copilot in Power BI aids the report development process. 

This course covers methods and practices to implement data engineering solutions by using Microsoft Fabric. Students will learn how to design and develop effective data loading patterns, data architectures, and orchestration processes. Objectives for this course include ingesting and transforming data and securing, managing, and monitoring data engineering solutions. This course is designed for data professionals with some data integration and orchestration experience.