Udemy – Apache Airflow 3 Scheduling: Trigger Pipelines & Data Assets

Mastering workflow orchestrations and automated pipeline triggers is the most critical skill for modern Data Engineers. Apache Airflow 3 redefines how data teams schedule, trigger, and manage complex enterprise data workflows. Whether you need to execute batch jobs on precise time schedules, run event-driven pipelines when S3 files land, or trigger workflows programmatically via REST APIs, this course delivers hands-on, practical expertise.

Who this course is for:

• Data Engineers looking to master Apache Airflow 3 scheduling and asset features
• Python Developers building automated ETL and ELT data pipelines
• Cloud Architects designing event-driven data platforms
• DevOps and MLOps Engineers orchestrating complex automation workflows

What you will learn:

• Configure time-based schedules with Cron expressions and custom Timetables
• Implement event-driven DAG triggers using Airflow 3 Data Assets
• Leverage Deferrable Operators and Sensors for resource-efficient execution
• Trigger workflows programmatically through the Airflow 3 REST API
• Build real-time event integration pipelines using Webhooks and Kafka
• Manage failure scenarios with retries, alerts, and fallback triggers
• Upgrade legacy Airflow 2 scheduling logic to Airflow 3 standards
• Design production-ready, enterprise-grade data pipeline architectures