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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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30 free minutes with a training advisor — no commitment.
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Explore the evolving role of artificial intelligence in crafting tailored educational journeys, with projections for groundbreaking advancements by April 2026.
Professional Training training in Memphis in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
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Don't let this gap widen
Sans maîtrise de Prefect, les data teams perdent 50% de temps en debugging manuel de pipelines, entraînant des retards de 2-3 semaines par projet critique.
Les échecs d'orchestration causent 20% de pertes de données annuelles, coûtant en moyenne 150 000€ par incident majeur en entreprise.
En 2024, 68% des offres data engineering exigent Prefect ou équivalent, écartant les profils non experts.
Chaque trimestre sans compétences avancées expose votre entreprise à des fuites concurrentielles et des audits conformité ratés.
The Formation Prefect - Orchestrer pipelines data scalables 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.
To ensure the quality of the Formation Prefect - Orchestrer pipelines data scalables training, Learni provides the following 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.
The assessment of skills acquired during the Formation Prefect - Orchestrer pipelines data scalables training is carried out through:
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.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Plongez dans la conception de flows Prefect complexes en utilisant des decorators Python avancés, mapping de tâches dynamiques et paramètres runtime, exercices pratiques sur des pipelines ETL réels avec données volumineuses, implémentez retries automatisés et gestion d'états partagés, testez des cas d'entreprise comme la synchronisation multi-sources, produisez un flow fil rouge scalable avec documentation complète et code review par le formateur pour une montée en compétences immédiate.
Déployez votre environnement Prefect en production via Docker et Kubernetes pour un scaling horizontal, configurez Prefect Server et agents hybrides avec intégrations cloud AWS/GCP, monitorez en temps réel via UI et métriques personnalisées, intégrez alertes Slack/Email sur échecs pipelines, exercices sur optimisation de coûts et haute disponibilité, finalisez le projet fil rouge avec migration d'un legacy Airflow, livrables incluent dashboards observabilité et plan de rollout entreprise pour booster vos compétences certifiantes.
Target audience
Data engineers, architectes data et DevOps data pour expertise en orchestration professionnelle
Prerequisites
Maîtrise avancée de Python, expérience en ETL/pipelines data et outils comme Airflow ou Dagster
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