Apache Airflow Best Practices equips data professionals with the skills to master Airflow, from foundational concepts to advanced deployment strategies. This course is essential for those wanting to build scalable data pipelines, optimize workflows, and leverage Airflow in cloud environments.

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Recommended experience
What you'll learn
Explore the new features and improvements in Apache Airflow 2.0
Design and build scalable data pipelines using DAGs
Implement ETL pipelines, ML workflows, and advanced orchestration strategies
Skills you'll gain
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December 2025
13 assignments
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There are 13 modules in this course
In this section, we explore data orchestration fundamentals, Airflow 2.0 features, and best practices for building scalable pipeline solutions.
What's included
2 videos2 readings1 assignment
In this section, we explore Apache Airflow's core concepts, including DAGs, task groups, and triggers, and how to implement them for efficient workflow automation and optimization.
What's included
1 video4 readings1 assignment
In this section, we explore Airflow components, their roles, and how to select and optimize executors for efficient workflow orchestration and scalability.
What's included
1 video4 readings1 assignment
In this section, we explore Airflow DAG authoring for API data extraction, focusing on task design with operators and workflow optimization for efficient data pipelines.
What's included
1 video4 readings1 assignment
In this section, we explore connecting Apache Airflow to external sources, designing DAGs with failure alerts, and managing secrets securely for efficient workflow automation.
What's included
1 video4 readings1 assignment
In this section, we cover creating Airflow UI plugins for custom workflow monitoring using Flask blueprints and metrics dashboards.
What's included
1 video1 reading1 assignment
In this section, we explore creating and distributing custom Airflow providers, focusing on structured packaging, testing, and reusable code for scalable workflow automation.
What's included
1 video3 readings1 assignment
In this section, we explore orchestrating machine learning workflows, focusing on DAG design, implementation, and MLOps practices for operational model deployment and performance analysis.
What's included
1 video2 readings1 assignment
In this section, we explore abstracting Airflow workflows to enable non-technical users to create and manage tasks. Key concepts include templated DAGs, workflow scheduling, and simplified orchestration for improved collaboration.
What's included
1 video2 readings1 assignment
In this section, we explore Airflow deployment strategies, DAG delivery patterns, and secure configuration management to optimize workflow efficiency and reliability.
What's included
1 video4 readings1 assignment
In this section, we explore monitoring strategies for Airflow systems and DAGs, focusing on core component health, DAG performance metrics, and alerting mechanisms for efficient workflow management.
What's included
1 video2 readings1 assignment
In this section, we explore strategies for implementing multi-tenancy in Airflow, focusing on isolation, operational requirements, and secure shared infrastructure management.
What's included
1 video1 reading1 assignment
In this section, we explore planning migration activities, implementing technical strategies, and executing pipeline changes with minimal downtime to ensure smooth Airflow transitions.
What's included
1 video1 reading1 assignment
Instructor

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Google Cloud
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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