Udemy – Apache Airflow 3 – The Complete Bootcamp [With Projects]

This is a COMPLETE Apache Airflow 3 Bootcamp you need in 2026 to become a PRO Apache Airflow Developer. Whether you’re a beginner or a working professional looking to upskill, this course will guide step by step with a hands-on, practical, and engaging lectures (doodle illustrations).

GAIN STRONG HANDS-ON WITH:

• Airflow Fundamentals & Architecture – Learn the fundamentals of Airflow and understand how DAG Processor, Metadata DB, Scheduler, Executor, Webserver, Workers work together to orchestrate data pipelines.
• DAG Authoring – Master the modern TaskFlow API to build complex DAGs with dependencies, branching, and subDAGs for real-world data workflows. Learn XCOMs and kwargs for inter-task communication and passing data between tasks in the DAGs.
• Operators & Hooks – Learn how to use built-in Operators and Hooks to interact with external systems like databases, APIs, and cloud services. Build custom connectors to integrate with any system.
• Scheduling & Triggers – Schedule your DAGs using Cron, Delta Triggers, Event-based triggers, and specific time intervals to cover a wide range of real-world use cases.
• Incremental Load & Backfilling – Implement incremental load strategies and backfill historical data to ensure your pipelines can handle both new and existing data effectively.
• Monitoring & Troubleshooting – Use the Airflow UI, logs, and metrics to monitor your DAGs, identify issues, and troubleshoot errors to ensure reliable pipeline execution.
• Security & Retries – Create connections in Airflow to securely store credentials for external systems. Implement error handling and retry mechanisms to ensure robust and fault-tolerant workflows.
• Airflow Assets & Scaling – Develop Airflow Assets to build data aware pipelines and manage data dependencies effectively. Scale Airflow with multiple workers and queues to distribute workload and optimize performance.
• End-to-End Projects – Additionally, build 2 real-world projects integrating AWS S3, Spark, Databricks, AWS Glue, APIs, and more to make your learning practical with real-world applications of Airflow.