1 Welcome to the course (56.6 MB) 2 Introduction to Apache Airflow (100.42 MB) 3 Understanding DAGs (Directed Acyclic Graphs) and operators (83.33 MB) 1 Final Project-1 (12.7 MB) 2 Final Project-2 (361.77 MB) 3 Final Project-3 (56.75 MB) 4 Final Project-4 (71.18 MB) 5 Final Project-5 (234.6 MB) 6 Course Closure (24.99 MB) 1 Components of Apache Airflow Scheduler, Executor, Metadata Database, Web Server (82.49 MB) 2 Understanding the role of each component in workflow orchestration (116.71 MB) 1 Installing Apache Airflow using different methods (e g , pip, Docker)-1 (114.38 MB) 2 Installing Apache Airflow using different methods (e g , pip, Docker)-2 (40.49 MB) 3 Exploring Airflow's web interface (66.08 MB) 1 Understanding DAGs in detail (150.03 MB) 2 How to Write DAGs (164.52 MB) 3 Best practices for organizing and managing DAG code (97.92 MB) 4 How to Write DAGs Assignment (18.05 MB) 1 Understanding Executors (114.74 MB) 2 Understanding different types of operators (BashOperator, PythonOperator, etc ) (203.19 MB) 3 Operators and Executors Assignment (15.46 MB) 1 Monitoring DAG runs and task statuses (264 MB) 2 Monitoring and Logging Assignment (15.55 MB) 1 Scaling Airflow horizontally and vertically (345.49 MB) 2 Configuring High Availability (HA) setups for production deployments-1 (161.53 MB) 3 Configuring High Availability (HA) setups for production deployments-2 (166.68 MB) 1 Working with sensors for external triggers and dependencies (182.39 MB) 2 Integrating Airflow with external systems (162.95 MB) 1 Writing unit tests for DAGs and tasks (116.72 MB) 2 Deployment and Best Practices (95.17 MB) 3 Practical Assignment (10.5 MB)
