Airflow Course
This course equips you with comprehensive skills to master Apache Airflow for data engineering. Learn to set up Airflow locally and with Docker, extract data via HTTP, transform using Python and Pandas, load into databases, monitor workflows, configure alerts, and implement best practices for reliable, production-ready ETL pipelines in modern data environments.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain expertise in installing, configuring, and operating Apache Airflow on local setups and Docker. Master building dependable ETL pipelines using HTTP sources, Python and Pandas for data processing, local databases, and Docker Compose. Develop skills in creating strong DAGs, error management, secure connections, monitoring, alerting, and production-grade best practices for efficient workflows.
Elevify advantages
Develop skills
- Design and build robust, parameterised ETL DAGs in Airflow for production use.
- Schedule, monitor, and debug data workflows effectively with Airflow tools.
- Extract and transform data reliably using HTTP APIs, Python, and Pandas libraries.
- Load data into databases with validation, idempotency, and schema verification.
- Implement monitoring, logging, security via RBAC, alerts, and best practices.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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