Delivered online or on-site, our instructor-led live Apache Airflow training courses provide an interactive, hands-on approach to constructing and maintaining comprehensive data pipelines.
You can access this Apache Airflow training in two formats: "online live training" or "onsite live training". The online live option (also referred to as "remote live training") utilizes an interactive remote desktop. For onsite live training, sessions are hosted directly at the client's location in Athens or within NobleProg's corporate training centers in Athens.
Take Metro Line 3 (M3) from Airport toward Dimotiko Theatro.
Get off at Evangelismos.
The address is on Vasilissis Sofias Avenue, very close to the station. Evangelismos station is directly on the avenue.
Allow roughly 40–50 minutes total, depending on waiting/walking time.
From Athens Central Railway Station (Larissa Station)
Take the metro to Syntagma and change to Line 3 toward Doukissis Plakentias/Airport.
Get off at Evangelismos.
Walk to No. 46.
By bus
There are several buses running along Vasilissis Sofias Avenue. Nearby stops include Rigilis Street and Syntagma, while the Evangelismos area is served by multiple bus routes.
The metro is generally the simplest option, especially if you're arriving with luggage.
This instructor-led, live training in Athens (online or onsite) is designed for advanced-level participants who aim to deploy Apache Airflow within cloud environments, establish CI/CD pipelines, and implement comprehensive monitoring and logging practices.
Upon completion of this training, participants will be able to:
Deploy Apache Airflow in cloud and containerized environments.
Establish CI/CD pipelines to automate DAG testing and deployment.
Integrate monitoring and logging tools to improve system reliability.
Optimize Airflow configurations for enhanced performance and scalability.
Apply security best practices for managing workflows and environments.
This instructor-led, live training in Athens (online or onsite) is designed for intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment using Apache Airflow.
By the end of this training, participants will be able to:
Set up Apache Airflow for machine learning workflow orchestration.
Automate data preprocessing, model training, and validation tasks.
Integrate Airflow with machine learning frameworks and tools.
Deploy machine learning models using automated pipelines.
Monitor and optimize machine learning workflows in production.
This instructor-led, live training in Athens (online or onsite) is aimed at advanced-level participants who wish to create custom operators, sensors, and plugins in Apache Airflow, and integrate these with existing data systems for advanced automation and monitoring.
By the end of this training, participants will be able to:
Develop custom operators, hooks, and sensors tailored to specific workflows.
Design and implement Airflow plugins to extend functionality.
Integrate Airflow workflows with external systems and services.
Optimize and monitor workflows using advanced debugging tools.
Leverage best practices for managing large-scale Airflow deployments.
This live, instructor-led training in Athens (online or onsite) is designed for intermediate-level participants seeking to optimize workflow performance, manage complex dependencies, and scale Apache Airflow deployments for larger datasets and enterprise use cases.
By the end of this training, participants will be able to:
Optimize Apache Airflow workflows for better performance and reliability.
Manage and troubleshoot complex workflow dependencies.
Leverage advanced Airflow features, including custom operators and sensors.
Scale Apache Airflow for handling larger data sets and distributed systems.
Implement best practices for monitoring, logging, and security in Airflow environments.
This instructor-led, live training in Athens focuses on Apache Airflow 2.x for the construction, automation, and scaling of data pipelines. Learners will acquire the skills to author DAGs, integrate cloud services, and deploy observability, security, and Kubernetes-based scaling to establish robust production environments.
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Testimonials (1)
The instructor adapted the training to the participants’ level and responded to all questions. He was very communicative, and it was easy to interact with him. I really appreciated the format of the training, which included many practical exercises. Overall, it was a very engaging and well-organized session.
Jacek Chlopik - ZAKLAD UBEZPIECZEN SPOLECZNYCH
Course - Apache Airflow: Building and Managing Data Pipelines
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