Features
Description
InfoShare Academy is a leading IT academy offering comprehensive educational programs in new technologies for companies. Since 2015, we have been supporting organizations in developing technology teams through dedicated courses in Machine Learning, DevOps, Data Engineering, Python, UX/UI Design, AWS, and Kubernetes. Our training is based on practical skills and real business cases. We collaborate with over 300 industry practitioners, ensuring that our programs are tailored to current market needs. We specialize in reskilling and upskilling employees. With us, you will build effective teams implementing new technologies that will accelerate innovation and strengthen your company's competitiveness in the market. Check out our training offerings designed for companies, created to enhance your employees' competencies in the IT field.
Apache Airflow is an advanced tool for scheduling and managing workflows in a big data environment. It allows for the creation, monitoring, and automation of business processes based on recurring and one-time tasks. Airflow enables the definition of dependencies between individual tasks and their automatic execution in the correct order, increasing the efficiency and reliability of business processes.
- For Data Scientists and those working with large amounts of data.
- For programmers with experience in Python.
- For programmers dealing with software infrastructure.
- For DevOps professionals.
- You will learn:
- Installation and configuration of the Apache AirFlow tool.
- The architecture and components used in AirFlow.
- How to create graphs (DAGs).
- Data passing with XCom, branching, and task organization.
Module 1 – Introduction
Historical overview (Airflow 1.0, Airflow 2.0)
Architecture overview (components)
Basic elements: DAG, instance, task
Module 2 – Creating graphs (DAGs)
Operators
Sensors
Hooks
Creating connections
Module 3 – Creating graphs (DAGs)
XCom – data passing
Branches – branching
Task organization – subDAG and groups
Creating connections
Additionally, the following elements will be covered:
Restarting DAGs
Resetting configuration
Catch option
Log verification
Optional modules to be implemented:
Building Airflow clusters (configuration of elements)
Using selected elements of DAGs
16 h/2 days
- Certificate of completion
- Monthly access to the training recording (in case of online format)
- Customization of the training program to client needs