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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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Cybersecurity training in Sheffield in November 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Cybersecurity training in Oklahoma City in December 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Artificial Intelligence training in Mesa in September 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Professional Training training in Tucson in December 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Don't let this gap widen
Sans maîtrise d'un Feature Store comme Feast, les pipelines ML d'entreprise génèrent des features inconsistantes, entraînant des modèles défaillants dans 70% des cas selon Gartner.
Cela se traduit par des pertes financières estimées à 15-20% sur les projets data, avec des retards de déploiement multipliés par trois et une gaspillage de ressources compute jusqu'à 40%.
Pour les administrateurs système et data engineers, ignorer ces outils expose à un risque carrière majeur : obsolescence face à la concurrence, turnover élevé et échecs projectuels récurrents.
Investissez dans cette formation novice pour sécuriser vos compétences et propulser la performance ML de votre équipe dès aujourd'hui.
The Formation Feature Store (Feast) - Maîtriser les bases ML en entreprise 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) - Maîtriser les bases ML en entreprise 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) - Maîtriser les bases ML en entreprise 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 les bases du Feature Store avec Feast lors de cette journée intensive en distanciel, installez l'outil via Docker en quelques minutes, configurez un registry de features dédié, ingérez des données réelles depuis des sources variées comme CSV ou bases SQL, testez des requêtes offline pour l'entraînement ML et online pour l'inférence, réalisez des exercices pratiques sur des cas concrets d'entreprise, produisez un pipeline fonctionnel comme livrable final, bénéficiez d'un feedback expert pour consolider vos compétences professionnelles dès la fin de la session.
Target audience
Administrateurs système, ingénieurs data, développeurs ML novices souhaitant une montée en compétences sur Feature Store pour optimiser les pipelines ML en entreprise.
Prerequisites
Connaissances de base en Python, notions de Docker et d'administration Linux.
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