Delivered either online or on-site, our instructor-led Apache Airflow courses offer an immersive, hands-on experience that empowers participants to construct and oversee comprehensive end-to-end data pipelines using Apache Airflow.
This training is available in two formats: "online live training" and "onsite live training." Online live sessions, also known as "remote live training," are conducted through an interactive remote desktop platform. Onsite live training takes place directly at your customer premises in Lille or within NobleProg’s corporate training centers located in Lille.
NobleProg -- Your Regional Training Partner
Lille, Gare Flandres
NobleProg Lille, 21 Avenue le Corbusier, Lille, france, 59800
In front of Flandres TGV Train Station
From Lille train stations
From Lille-Flandres: the address is essentially right next to the station — about 1–3 minutes on foot.
From Lille-Europe: walk toward Lille-Flandres along Avenue Le Corbusier. It is roughly 5–10 minutes on foot.
So you don't need a bus or metro if you're arriving by train.
If you're coming by bus
The nearest bus stops to Avenue Le Corbusier include Lion d'Or and Jacquet. Several local lines serve the area, including 13, 86, L5 and L91.
This instructor-led live training in Lille (online or onsite) is aimed at advanced-level participants who wish to deploy Apache Airflow in cloud environments, set up CI/CD pipelines, and implement robust monitoring and logging practices.
By the end of this training, participants will be able to:
Deploy Apache Airflow in cloud and containerized environments.
Set up CI/CD pipelines to automate DAG testing and deployment.
Integrate monitoring and logging tools to enhance system reliability.
Optimize Airflow configurations for performance and scalability.
Implement security best practices for managing workflows and environments.
This instructor-led live training, held in Lille (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 Lille (online or onsite) is targeted at advanced participants seeking to build custom operators, sensors, and plugins within Apache Airflow, and to integrate these components with existing data systems for enhanced automation and monitoring capabilities.
Upon completion 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 instructor-led, live training in Lille (online or on-site) targets intermediate-level participants seeking to optimize workflow performance, manage complex dependencies, and scale Apache Airflow deployments for larger datasets and enterprise use cases.
Upon completion of this training, participants will be able to:
Optimize Apache Airflow workflows to enhance performance and reliability.
Manage and troubleshoot complex workflow dependencies.
Leverage advanced Airflow features, including custom operators and sensors.
Scale Apache Airflow to handle larger data sets and distributed systems.
Implement best practices for monitoring, logging, and security in Airflow environments.
This instructor-led, live training in Lille focuses on Apache Airflow 2.x for the construction, automation, and expansion of data pipelines. Learners will master the creation of DAGs, integration of cloud services, and the implementation of 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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