Workflow Automation with Airflow: Building Reliable Data Pipelines

Data pipelines are the backbone of modern data engineering, but managing complex dependencies manually is prone to errors. This text-based course introduces you to Airflow, the industry-standard platform for orchestrating, scheduling, and monitoring workflows. You will transition from manual script execution to designing automated, resilient data pipelines. By studying clear written explanations, analyzing code snippets, and completing practical exercises, you will master the core concepts of pipeline orchestration. What you'll learn: - Understand core Airflow concepts including DAGs, operators, tasks, and scheduling - Write clean pipeline definitions using the modern TaskFlow API - Manage connections, variables, and sensitive credentials securely - Implement robust error handling, retries, and alerting mechanisms - Schedule and monitor complex workflows with dynamic task mapping - Apply best practices for idempotency and data pipeline reliability This course begins with fundamental terminology and basic architecture before moving step-by-step through pipeline design and deployment strategies. Designed for aspiring data engineers and developers, this course requires no prior Airflow experience, though basic Python familiarity is helpful. Start building reliable automated workflows today.