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 AWS MWAA - Orchestrer workflows data avec Airflow sur AWS training are: Connaissances en Python, bases AWS (S3, IAM, VPC), notions d'Apache Airflow et DAGs. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Formation AWS MWAA - Orchestrer workflows data avec Airflow sur AWS training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Formation AWS MWAA - Orchestrer workflows data a... | 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 AWS MWAA - Orchestrer workflows data avec Airflow sur AWS 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 AWS MWAA - Orchestrer workflows data avec Airflow sur AWS 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 AWS MWAA - Orchestrer workflows data avec Airflow sur AWS 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

Maîtriser AWS MWAA pour déployer des environnements Apache Airflow managés en entreprise

Développer des DAGs avancés et optimisés pour des workflows data professionnels

Configurer l'intégration d'AWS MWAA avec S3, EMR et Lambda pour des pipelines scalables

Implémenter le monitoring et la sécurisation des workflows Airflow certifiants

Optimiser les performances et le scaling d'AWS MWAA dans des contextes production

Concevoir des architectures data robustes avec compétences Apache Airflow sur AWS

Training program

Module 1Fondamentaux AWS MWAA : configuration d'environnement Apache Airflow managed (S3, IAM, VPC)

Découverte approfondie d'AWS MWAA via la console AWS, création d'un environnement Airflow managed en quelques clics, configuration des buckets S3 pour DAGs et logs, mise en place des rôles IAM sécurisés et VPC pour l'isolation réseau, premiers tests de DAGs simples sur des datasets réels, exercices pratiques pour valider le déploiement rapide d'un workflow data professionnel, production d'un environnement fonctionnel prêt pour l'entreprise.

Module 2Développement DAGs avancés AWS MWAA : orchestration complexe avec operators AWS (EMR, Glue, Lambda)

Conception de DAGs multi-tâches intégrant operators AWS natifs comme BashOperator, EmrStepOperator et LambdaInvoke, utilisation de XCom pour passer des données entre tâches, gestion des dépendances dynamiques et des erreurs avec retries intelligents, ateliers pratiques sur un cas concret de pipeline ETL e-commerce, optimisation des performances via parallelism et pooling, génération de DAGs testés et déployés directement dans votre environnement MWAA pour une montée en compétences immédiate.

Module 3Production AWS MWAA : monitoring, scaling et sécurisation Apache Airflow (CloudWatch, secrets backend)

Implémentation du monitoring avancé avec CloudWatch et Airflow UI personnalisée, configuration du scaling automatique pour pics de charge data, sécurisation via Fernet et AWS Secrets Manager pour variables sensibles, gestion des déploiements CI/CD avec GitSync, simulations d'incidents réels pour drills de résilience, finalisation d'un projet fil rouge scalable et monitoré, remise de blueprints prêts à l'emploi pour booster vos compétences professionnelles en entreprise.