Data Engineering with Copilot in Fabric: A Practical Guide

Modern data engineering moves fast, and writing complex data transformation pipelines from scratch can be time-consuming. This course introduces you to Copilot in Fabric, an AI-powered assistant designed to streamline your data workflows and boost your productivity. You will transition from manual coding to smart, AI-assisted data engineering. Through clear explanations and written exercises, you will learn how to write effective prompts that generate clean PySpark code, debug errors, and optimize data pipelines within your lakehouse environment. What you'll learn: - Understand the core architecture of Fabric and how Copilot integrates with data engineering workloads - Formulate precise prompts to generate, explain, and document PySpark code automatically - Clean and transform raw datasets using AI-guided notebook operations - Debug code errors and optimize pipeline performance with intelligent suggestions - Apply modern data engineering practices, including basic data profiling and schema validation The course begins with foundational concepts of cloud-based data engineering and the role of generative AI in analytics. You will then progress through step-by-step written scenarios, learning how to leverage Copilot for real-world data preparation, transformation, and optimization tasks. This course is designed for aspiring data engineers, database administrators, and data analysts who want to integrate AI assistance into their workflow. No prior experience with generative AI or advanced data engineering is required, though a basic understanding of data concepts is helpful. Start reading today to transform your data engineering workflow with the power of smart AI assistance.