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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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Don't let this gap widen
Sans maîtrise du traitement avancé du langage naturel avec spaCy en Python, vos pipelines d'analyse de texte génèrent des erreurs récurrentes et des résultats inexacts.
Les data scientists non experts perdent en moyenne 40 % de temps sur les projets NLP, soit 20 000 € de productivité annuelle par développeur, freinant les lancements de produits.
75 % des incidents en automatisation textuelle proviennent d'une mauvaise implémentation spaCy, exposant l'entreprise à des pertes clients et des amendes RGPD jusqu'à 50 000 €.
Chaque trimestre sans compétences avancées, votre équipe rate des opportunités IA critiques, menaçant sa compétitivité et votre ascension professionnelle.
The Maîtriser spaCy : Traitement Avancé du Langage Naturel en Python 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 spaCy : Traitement Avancé du Langage Naturel en Python 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 spaCy : Traitement Avancé du Langage Naturel en Python 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.
Présentation du NLP et de spaCy, installation et configuration, architecture des pipelines, exploration des objets Doc, Token et Span. Premiers scripts : analyse de textes, segmentation, visualisation.
Étude approfondie de la tokenisation et de la gestion multilingue. Analyse morphosyntaxique (POS-tagging, dépendances). Reconnaissance des entités nommées (NER) avec spaCy, visualisation et extraction automatisée d’entités. Exercices d’application sur des cas concrets (CV, articles, retours client).
Création et entraînement de modèles sur vos propres jeux de données (annotation de données, création de pipelines spécifiques, extension via spaCy Universe). Ajout de composants personnalisés, intégration à des workflows Python (API, scripts batch). Bonnes pratiques, debugging et performance. Étude de cas professionnel (veille automatisée, extraction de connaissance métier, intégration cloud/déploiement).
Target audience
Développeurs, data scientists, ingénieurs data ou analystes souhaitant automatiser l’analyse de texte avec spaCy dans Python
Prerequisites
Connaissances de base en Python et notions fondamentales en traitement de texte
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