Abstract: With a lot of changes under the hood with Airflow 2.0, the workshop aims to give an overview on major updates in Airflow 2.0 from 1.0, major components and working of Airflow and hands-on demo of implementation and management of an end-to-end Machine Learning pipeline. Without a pipeline in-place, management of multiple Machine Learning stages in production can be difficult. This gives an overview of simplified process and management of Python based ML projects using Airflow. 05 min: Introduction 05 min: Major changes in Airflow 2.0 05 min: Pre-requisites setup overview 10 min: Walkthrough of different backend components 10 min: Different stages of a DAG file – steps and operators 10 min: Dynamic DAG creation to improve parallelism 15 min: How to trigger Airflow DAG runs 15 min: Debug and clear Airflow task errors 10 min: Overview of production-level Airflow-based architecture 05 min: Wrap up questions For more details: https://pretalx.com/pycon-sweden-2021/talk/JRCLRG/ Speaker: Alen Jacob