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Apache Airflow Course Overview

Apache Airflow Course Overview

Unlock the power of workflow automation with our comprehensive Apache Airflow course at Koenig Solutions. Begin with a solid foundation through an Introduction to Apache Airflow, understanding its role in managing complex workflows effectively. You'll learn to set up Airflow with ease, covering installation, configuration, and basic operations. Dive deep into Core Concepts including Directed Acyclic Graphs (DAGs), and discover how to create and manage scalable workflows with advanced features such as SubDAGs, Branching, and Conditional Logic. Enhance your skills in Monitoring and Troubleshooting to ensure optimum performance. The course also includes practical labs for hands-on experience, setting you up to efficiently integrate Airflow into your business processes. This training enables participants to apply learned concepts practically, ensuring they can manage and optimize Airflow deployments in real-world scenarios.

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  • Live Training (Duration : 32 Hours)
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Target Audience for Apache Airflow

Introduction to Apache Airflow Course: This course equips participants with skills in managing and automating data workflows using Apache Airflow, catering primarily to IT professionals in data-oriented roles.


Target Audience:


  • Data Engineers
  • DevOps Engineers
  • Software Developers involved in Data-intensive applications
  • System Administrators managing data pipelines
  • Data Scientists needing workflow automation
  • IT Project Managers overseeing data projects
  • Cloud Engineers working with data-driven cloud services
  • Technical Architects designing data flow strategies


Learning Objectives - What you will Learn in this Apache Airflow?

Introduction to the Course's Learning Outcomes and Concepts Covered

This Apache Airflow course equips students with the skills to design, implement, and manage workflow automation using Airflow, covering installation, core concepts, advanced features, and integration.

Learning Objectives and Outcomes

  • Understand the fundamental concepts of workflow management systems and the role of Apache Airflow.
  • Install and configure Apache Airflow, including setting up the necessary infrastructure like the web server and scheduler.
  • Grasp core Airflow concepts such as Directed Acyclic Graphs (DAGs), Operators, Sensors, and Executors.
  • Develop skills in writing DAGs, using operators to define tasks, and setting task dependencies.
  • Employ advanced Airflow features like SubDAGs, TaskGroups, branching, conditional logic, and triggering rules.
  • Implement hands-on workflow creation, from simple to complex DAGs, including dynamic dependency management and cross-DAG dependencies.
  • Monitor, troubleshoot, and optimize Airflow deployments, including configuring logging, handling retries, and scaling for production.
  • Apply best practices for high availability, security, and fault-tolerant deployment of Airflow.
  • Integrate Airflow with external systems like databases and cloud services to enhance workflow capabilities.
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