Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Formation Airflow - Orchestrez vos pipelines data efficacement training are: Maîtrise de Python, bases en SQL, expérience initiale avec Airflow ou un outil d'orchestration similaire.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Formation Airflow - Orchestrez vos pipelines data efficacement training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Formation Airflow - Orchestrez vos pipelines dat... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Formation Airflow - Orchestrez vos pipelines data efficacement training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Formation Airflow - Orchestrez vos pipelines data efficacement training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Formation Airflow - Orchestrez vos pipelines data efficacement training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training objectives

Configurer un environnement Airflow scalable en production

Développer des DAGs complexes avec dépendances et paramètres dynamiques

Gérer les erreurs, retries et XComs pour des workflows robustes

Intégrer opérateurs personnalisés et hooks avec des outils data externes

Implémenter monitoring, alertes et optimisation des performances

Déployer Airflow sécurisé avec Celery et Kubernetes

Training program

Module 1Installation et configuration : setup Airflow avec Docker, metadata DB, workers Celery

Installez Airflow en mode distribué via Docker, configurez la base metadata et les connections sécurisées, lancez des workers pour scaler, réalisez des exercices sur variables et pools, testez un premier DAG simple, produisez un environnement de test fonctionnel prêt pour des pipelines réels, gagnez en autonomie immédiate.

Module 2DAGs avancés : tâches conditionnelles, SubDAGs, paramètres dynamiques

Concevez des DAGs complexes avec branches conditionnelles et triggers, implémentez des SubDAGs pour modularité, paramétrez dynamiquement via macros et templates Jinja, pratiquez sur cas ETL réels comme ingestion data warehouse, générez des livrables testables, transformez vos idées en workflows automatisés performants.

Module 3Opérateurs et erreurs : hooks personnalisés, retries intelligents, XComs

Maîtrisez opérateurs Bash, Python, Postgres et custom, intégrez hooks pour APIs externes comme S3 ou Kafka, gérez erreurs avec retries adaptatifs et backfills, transférez données via XComs, appliquez sur exercices de data pipeline défaillant, créez des tâches résilientes, boostez la fiabilité de vos automatisations.

Module 4Monitoring et déploiement : UI avancée, alertes Slack, scaling Kubernetes

Exploitez l'interface web pour debug et audits, configurez alertes Slack et Grafana, optimisez scheduler et executor, déployez sur Kubernetes avec Helm, finalisez un projet capstone complet sur pipeline end-to-end, mesurez gains en temps et ROI, repartez avec expertise production-ready.