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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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No-Code / Low-Code training in Leeds in November 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Discover the best warehouse management and logistics training options scheduled for March 2026, focusing on emerging trends like AI automation, sustainability, and supply chain resilience to boost your career.
Artificial Intelligence training in Raleigh in June 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Professional Training training in Dallas in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Don't let this gap widen
Sans maîtrise de Weaviate, les projets de recherche sémantique virent au cauchemar : implémentations laborieuses multipliées par 3 en temps de développement.
65 % des incidents en IA générative proviennent d'une mauvaise gestion vectorielle, générant des pertes moyennes de 80 000 € par projet défaillant en faux positifs ou recherches imprécises.
Votre entreprise sacrifie alors 25 % de sa compétitivité sur le marché des données intelligentes, exposant managers et devs à des carrières bloquées face à la vague des vector DB.
Chaque mois sans ces fondamentaux creuse un retard cumulatif de 15 000 € en opportunités manquées.
The Maîtriser Weaviate : Les Fondamentaux de la Base de Données Vectorielle Open Source 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 Maîtriser Weaviate : Les Fondamentaux de la Base de Données Vectorielle Open Source 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 Maîtriser Weaviate : Les Fondamentaux de la Base de Données Vectorielle Open Source 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.
Panorama des bases de données vectorielles. Découverte de Weaviate, ses cas d’usage : recherche sémantique, recommandations, IA générative. Installation de Weaviate (local, Docker, cloud), tour d’horizon de l’interface, prise en main des outils essentiels.
Définir un schéma (Classes, Propriétés, Relations). Différence entre schéma relationnel/NoSQL et schéma vectoriel. Création de premiers schémas, manipulation via API GraphQL et REST, importation de données (CSV, JSON, données textuelles/langage naturel). Génération de vecteurs : connecteurs, modèles embarqués, intégration avec HuggingFace.
Création et exécution de requêtes sémantiques avancées : recherche par similarité, filtrage, hybrid search (mot-clef + sémantique). Opérations de mise à jour et de suppression. Intégration avec un projet Python : requêtage via SDK/HTTP. Sécurité, gestion des utilisateurs, backup/restauration. Bonnes pratiques de monitoring & scaling pour un usage production.
Target audience
Développeurs, data scientists et professionnels cherchant à exploiter les potentialités des bases de données vectorielles pour la recherche sémantique
Prerequisites
Connaissances de base en Python et notions générales sur les bases de données relationnelles ou NoSQL
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