Building Data Pipelines in Python

Processing raw information into structured, actionable insights is a foundational skill across software development and data engineering. This text-based course guides you through creating modular, reliable data pipelines from the ground up using functional programming principles and clean code architecture. What you'll learn: - Understand core data engineering terminology, pipeline architectures, and data flow patterns - Apply functional programming techniques, closures, and first-class functions to data manipulation - Build reusable Python decorators to manage logging, performance timing, and error handling - Design flexible pipeline interfaces with modern Python type hints for maintainable code - Practice testing pipeline components and validation rules using pytest - Construct an end-to-end pipeline that extracts, parses, filters, and summarizes real-world structured datasets The material begins with fundamental concepts and functional programming essentials before moving into hands-on code walkthroughs and modular pipeline construction. This course is ideal for beginners and aspiring data engineers who have basic Python knowledge and want to learn practical data workflow development. Start reading today and master the foundations of reliable data pipelines.