Interactive Course

Introduction to Airflow in Python

Learn how to to implement and schedule data engineering workflows.

  • 4 hours
  • 16 Videos
  • 55 Exercises
  • 2,993 Participants
  • 4,050 XP

Loved by learners at thousands of top companies:


Course Description

Are you responsible for delivering data on a schedule? You may have written scripts, added complex cron tasks, and tried various ways to meet an ever-changing set of requirements. It's even trickier to work with your teammates on managing multiple sets of requirements. Airflow can do this while adding scheduling, error handling, and reporting. Introduction to Airflow in Python will guide you in the basic concepts of Airflow and help you implement data engineering workflows in production. You'll implement many different data engineering tasks in a sane, repeatable fashion, while losing as little sanity as possible.

  1. 1

    Intro to Airflow


    An introduction to the components of Apache Airflow and why to use them.

  2. Implementing Airflow DAGs

    Learn the basics of implementing Airflow DAGs using operators, tasks, and scheduling.

  3. Maintaining and monitoring Airflow workflows

    Learn more about Airflow components such as sensors and executors while monitoring and troubleshooting Airflow workflows.

  4. Building production pipelines in Airflow

    Use what you've learned to build a production quality workflow in Airflow.

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Mike Metzger
Mike Metzger

Data Engineer Consultant @ Flexible Creations

Mike is a consultant focusing on data engineering and analysis using SQL, Python, and Apache Spark among other technologies. He has a 20+ year history of working with various technologies in the data, networking, and security space.

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  • Hadrien Lacroix

    Hadrien Lacroix

  • Lis Sulmont

    Lis Sulmont

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