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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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Artificial Intelligence training in San Francisco in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
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Professional Training training in Fort Worth in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Don't let this gap widen
Sans pgvector 2026, vos recherches sémantiques restent limitées à Elasticsearch lent, perdant 70% en vitesse sur datasets >1M vecteurs selon benchmarks ANN.
Les entreprises subissent des coûts cloud explosifs, jusqu'à 40% plus élevés sans index vectoriels natifs Postgres, et ratent 25% des opportunités IA comme le RAG efficace.
Carrières stagnent : data engineers sans pgvector peinent face à la demande +300% en vector DB (source StackOverflow 2025).
Risquez-vous l'obsolescence ?
Maîtrisez pgvector dès maintenant pour scaler vos apps IA en production sécurisée.
The Formation pgvector 2026 - Optimiser recherches vectorielles Postgres 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 pgvector 2026 - Optimiser recherches vectorielles Postgres 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 pgvector 2026 - Optimiser recherches vectorielles Postgres 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 native de pgvector 2026 sur clusters Kubernetes, configurez les extensions avec Docker Compose pour tests rapides, implémentez des index HNSW pour similarités cosine/euclidiennes, testez avec datasets millionnaires d'embeddings OpenAI, générez vos premiers vecteurs via pgml et pgvector, analysez logs de performance en temps réel, produisez un setup reproductible avec Ansible pour déploiements enterprise.
Plongez dans les queries vectorielles complexes avec knn/lnnp, combinez SQL et vecteurs pour recherches hybrides text/image, intégrez LangChain et pgvector pour RAG low-latency, optimisez avec approximate nearest neighbors sur GPU, simulez charges 10k QPS via pgbench custom, déboguez bottlenecks avec EXPLAIN ANALYZE vectoriel, livrez un prototype RAG full-stack connecté à votre SGBD existant.
Maîtrisez le sharding vectoriel avec Citus+pgvector 2026, déployez monitoring Prometheus/Grafana pour métriques latency/throughput, sécurisez accès via Row Level Security sur embeddings sensibles, intégrez backups incrémentaux vectoriels, testez failover haute disponibilité en live, optimisez coûts AWS/GCP avec auto-scaling, finalisez un dashboard opérationnel et un plan de migration pour votre entreprise.
Target audience
Data engineers, architectes bases de données, experts ML et DevOps en entreprise pour monter en compétences sur vector search scalable
Prerequisites
Maîtrise PostgreSQL 16+, embeddings vectoriels, Python/SQL avancés, machine learning opérationnel
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