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In this course, you will learn :
- Create plugins to extend the functionality of Apache Airflow.
- Docker with Airflow and various executors
- Understand core functionalities such as DAGs, Operators, Tasks, Workflows, and so on.
- Understand and apply advanced Apache Airflow concepts such as XCOMs, Branching, and SubDAGs.
- The distinction between Sequential, Local, and Celery Executors, how they work, and how they can be used.
- Use Apache Airflow in a Big Data ecosystem alongside Hive, PostgreSQL, Elasticsearch, and other databases.
- Apache Airflow must be installed and configured.
- Consider, respond to, and implement Airflow-based solutions to real-world data processing problems.
Syllabus :
- Course Introduction
- Getting Started with Airflow
- Coding Your First Data Pipeline with Airflow
- Databases and Executors
- Implementing Advanced Concepts in Airflow
- Creating Airflow Plugins with Elasticsearch and PostgreSQL
- Using Apache Airflow with Docker
- Airflow 2.0
