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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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Cybersecurity training in Oklahoma City in December 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Allan Busi
Dec 1, 20269 min readOklahoma City
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Allan BusiJul 1, 20268 min readDallasDon't let this gap widen
Sans maîtrise d'un feature store comme Feast 2026, 70% des projets ML échouent en phase de production selon Gartner, gaspillant des millions en retravail ETL et features obsolètes.
Les data teams perdent 40% de temps sur data drift non détecté, impactant ROI jusqu'à -25% sur modèles prédictifs.
Carrières stagnent : data engineers sans compétences feature store peinent à scaler pipelines, risquant obsolescence face à la demande explosive (marché +50% annuel).
Entreprises subissent concurrence féroce sans centralisation features, menant à silos data coûteux.
Investissez dès maintenant pour sécuriser performances ML et avancement pro.
The Formation Feature Store (Feast) 2026 - Centraliser features pour ML scalable 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 Feature Store (Feast) 2026 - Centraliser features pour ML scalable 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 Feature Store (Feast) 2026 - Centraliser features pour ML scalable 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.
Découvrez l'installation rapide de Feast 2026 via Docker et cloud providers, configurez les providers comme Snowflake ou BigQuery pour des environnements professionnels, créez vos premières feature views et entities avec des exercices pratiques sur datasets réels, explorez la CLI Feast pour valider et tester les définitions, générez des registries locaux puis distants, et terminez par un cas concret de materialization offline, livrant un prototype fonctionnel prêt pour l'équipe data.
Plongez dans les pipelines hybrides online/offline avec Feast serving pour low-latency inference, intégrez à Kubernetes et Spark pour scaler en production, mettez en place la gouvernance via lineage et versioning des features, pratiquez des exercices sur monitoring et debugging avec Prometheus, connectez Feast à MLflow et Tecton-like workflows, simulez un déploiement entreprise complet, et validez avec un projet livrable certifiant, renforçant vos compétences en feature store opérationnel.
10 participants max.
$2,420 / per person
2 days
distancielTarget audience
Data engineers, ML engineers, data scientists et architectes de données cherchant une montée en compétences sur les feature stores pour optimiser les pipelines ML en entreprise
Prerequisites
Maîtrise de Python, notions en machine learning, expérience en gestion de données et ETL
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Intermédiaire
€4,200.004 journées
distanciel10 pers. max.Intermédiaire€5,250.005 journéesdistanciel10 pers. max.Expert€2,100.002 journéesdistanciel10 pers. max.Novice€5,250.005 journéesdistanciel10 pers. max.
