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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.
Explore the evolving role of artificial intelligence in crafting tailored educational journeys, with projections for groundbreaking advancements by April 2026.
Professional Training training in Dallas in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Artificial Intelligence training in Raleigh in June 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Don't let this gap widen
Sans maîtrise du Deep Learning appliqué à la Vision par Ordinateur avec Ultralytics, 70% des projets d'IA échouent en phase de déploiement, d'après des études IDC.
Cela engendre une perte moyenne de 150 000 € par initiative ratée, avec des retards cumulés de 4 à 6 mois en production.
Vos équipes gaspillent 50 heures par mois en debugging inefficace, exposant l'entreprise à des faux positifs critiques en surveillance ou manufacturing, et menaçant directement votre avancement professionnel.
Chaque trimestre sans compétences avancées amplifie la vulnérabilité concurrentielle, risquant une érosion de 20% des parts de marché.
The Ultralytics : Maîtriser le Deep Learning appliqué à la Vision par Ordinateur 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 Ultralytics : Maîtriser le Deep Learning appliqué à la Vision par Ordinateur 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 Ultralytics : Maîtriser le Deep Learning appliqué à la Vision par Ordinateur 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 de la bibliothèque Ultralytics et de ses usages en vision par ordinateur. Historique des modèles YOLO. Concepts fondamentaux de la détection d’objets. Installation de l’environnement (Python, gestionnaire de paquets, GPU). Prise en main des notebooks Ultralytics.
Collecte, annotation et organisation des jeux de données (formats YOLO et COCO). Méthodes de data augmentation. Utilisation de l’outil Ultralytics LabelImg. Entraînement d’un premier modèle sur un dataset d’exemple. Suivi des métriques, interprétation des logs d’entraînement.
Techniques d’optimisation (hyperparamètres, callbacks, scheduler). Fine-tuning sur jeux de données spécifiques. Export de modèles (ONNX, TorchScript). Déploiement en production : APIs REST, applications mobiles et edge computing. Bonnes pratiques pour l’évaluation et l’amélioration de la robustesse. Étude de cas réel et atelier pratique de détection d’objets sur un projet concret.
Target audience
Développeurs, data scientists, ingénieurs, chefs de projet IT et toute personne souhaitant implémenter des solutions de vision par ordinateur avec Ultralytics
Prerequisites
Bases en Python et notions fondamentales en intelligence artificielle et machine learning.
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