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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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Explore the evolving role of artificial intelligence in crafting tailored educational journeys, with projections for groundbreaking advancements by April 2026.
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Don't let this gap widen
Sans maîtrise des fondamentaux de la reconnaissance en IA, 80 % des projets informatiques échouent dès la phase de développement, gaspillant en moyenne 6 mois de travail et 150 000 € par initiative ratée.
Les faux positifs et négatifs génèrent des incidents critiques, comme des erreurs de détection coûtant jusqu'à 500 000 € en pertes business pour les data scientists et développeurs impliqués.
Votre entreprise perd 25 % de parts de marché face à des concurrents agiles, tandis que votre carrière s'enlise dans des échecs récurrents.
Chaque retard amplifie les risques, rendant l'inaction intenable.
The Maîtriser les Fondamentaux de la Reconnaissance dans l’Intelligence Artificielle 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 les Fondamentaux de la Reconnaissance dans l’Intelligence Artificielle 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 les Fondamentaux de la Reconnaissance dans l’Intelligence Artificielle 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.
Définitions et grands principes. Panorama des domaines : reconnaissance d’images, faciale, vocale, textes, objets. Histoire et évolution de la reconnaissance par l’IA. Cas d’application dans la vie réelle : sécurité, industrie, loisirs, assistance aux personnes, marketing.
Fonctionnement des systèmes de reconnaissance. Présentation des algorithmes classiques de reconnaissance (k-NN, SVM, arbres de décision). Introduction aux réseaux de neurones et deep learning pour la reconnaissance. Prise en main des outils : OpenCV, scikit-learn, TensorFlow/Keras. Exercices pratiques : installation, premiers algorithmes, jeu de données MNIST.
Développement d’un mini-projet de reconnaissance (vision ou NLP selon l’intérêt). Analyse des performances : matrice de confusion, précision, rappel, F-mesure. Présentation des limites, biais possibles, questions de vie privée et éthique. Étude de cas réels et débats. Conseils pour continuer à progresser dans le domaine et veille technologique.
Target audience
Professionnels de l'informatique, développeurs, data scientists, enseignants, ou toute personne souhaitant maîtriser les techniques de reconnaissance par l’IA.
Prerequisites
Avoir des bases en algorithmique et programmation (Python recommandé)
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