What you'll learn
Understand the features and benefits of using Airflow for workflow orchestration.
Acquire troubleshooting skills for common installation issues and debugging setup problems
Understand the architecture and components of Apache Airflow.
Develop skills in handling complex dependencies and parallelism in DAG design.
Implement custom operators and sensors for seamless integration with specific systems or APIs.
Leverage XCom for efficient data exchange between tasks.
Develop skills in designing complex SubDAGs and managing dynamic workflow structures.
Implement Incremental Data Processing with a custom Airflow Operator.

Requirements
Any python version which is above 3.7 preferably pycharm
Latest version of Visual Studio Code application
Basic knowledge of python

Description
This course is meticulously crafted to provide you with a deep understanding of Apache Airflow, from the fundamentals to advanced concepts. Whether you're a beginner or a seasoned professional, this course equips you with the skills needed to orchestrate complex data workflows efficiently.Module 1: Introduction and Installation Embark on your Airflow journey with a solid foundation. Gain insights into Airflow's features and benefits, and master the art of installing and configuring Airflow in various environments. Dive into challenging resolution topics, troubleshooting installation issues, and debugging setup problems.Module 2: Workflow Design and Management Explore the intricacies of Airflow's architecture and components. Learn to define and structure workflows using Directed Acyclic Graphs (DAGs). Grasp task dependencies, scheduling techniques, and how to manage workflow execution, retries, and Service Level Agreements (SLAs). Tackle challenges in handling complex dependencies and parallelism in DAG design.Module 3: Operators and Sensors Navigate the diverse world of operators in Airflow, including BashOperator, PythonOperator, and SQLOperator. Harness the power of sensors to trigger tasks based on external events or conditions. Confront challenges by implementing custom operators and sensors for seamless integration with specific systems or APIs.Module 4: Advanced Concepts and Scaling Elevate your expertise with advanced workflow concepts, such as SubDAGs and branching workflows. Leverage XCom for efficient data exchange between tasks. Work with connections and variables in Airflow, and scale Airflow to handle large workloads while optimizing performance. Create a machine learning framework for executing specific tasks within the workflow. Conquer challenges in designing complex SubDAGs and managing dynamic workflow structures.Module 5: Incremental Data Load Delve into Incremental Data Processing and understand efficient strategies. Learn to implement Incremental Data Processing with a custom Airflow Operator. Explore techniques for efficient transformation and loading, ensuring optimal data processing strategies.Enroll now to unlock the full potential of Apache Airflow, conquer challenges, and become a master orchestrator of data workflows!

Who this course is for
Aspiring Data Engineers
ETL developers
Data Scientists
Data Analysts
Software Engineers
Enterprise Architects