Apache Airflow Tutorials

The Apache Airflow Tutorials course is designed to teach individuals how to use Apache Airflow, an open-source platform for programmatically authoring, scheduling, and monitoring workflows. The course is suitable for anyone interested in learning how to automate and streamline their data pipelines and workflows. The course covers the basics of Apache Airflow, including its architecture, components, and terminology. It also delves into more advanced topics, such as creating custom operators, sensors, and hooks, and integrating with external systems such as databases and cloud services. One of the key features of Apache Airflow is its ability to create, schedule, and monitor workflows as directed by the user. In this course, learners will learn how to use the platform to create and manage workflows using Python code, which allows for maximum flexibility and customization. Additionally, the course covers the use of Airflow's user interface, which provides a graphical representation of workflows, tasks, and dependencies, making it easier to visualize and manage complex workflows. The course also covers best practices for managing workflows in Apache Airflow, including error handling, logging, and scaling. Learners will also explore the integration of Airflow with other popular tools, such as Kubernetes and Docker, for deploying and managing workflows in a containerized environment. Throughout the course, learners will have access to practical examples and exercises, which will help reinforce their understanding of Apache Airflow concepts and techniques. The course is suitable for both beginners and experienced users looking to expand their knowledge of the platform. By the end of the Apache Airflow Tutorials course, learners will have a solid foundation in using Apache Airflow for creating, scheduling, and monitoring workflows. They will have the knowledge and skills needed to automate their data pipelines and workflows, streamline their processes, and improve overall efficiency. Author: Tuan Vu (YouTube)