Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Maîtriser TensorFlow : De l’initiation à la pratique avancée de l’IA training are: Notions de programmation Python, bases en mathématiques (algèbre linéaire, statistiques). A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Maîtriser TensorFlow : De l’initiation à la pratique avancée de l’IA training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Maîtriser TensorFlow : De l’initiation à la prat... | Learni

The story of Learni

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.

Configure your training

Response within 24hNo commitment100% free

7 spots remaining for the next session

FormatParticipantsDateDetails

Which format do you prefer?

Methods, approaches, and teaching resources

The Maîtriser TensorFlow : De l’initiation à la pratique avancée de l’IA 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.

Teaching resources provided

To ensure the quality of the Maîtriser TensorFlow : De l’initiation à la pratique avancée de l’IA training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and 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.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Maîtriser TensorFlow : De l’initiation à la pratique avancée de l’IA training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

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.

Training objectives

Comprendre les concepts fondamentaux de TensorFlow et du machine learning

Installer, configurer et utiliser TensorFlow pour des projets réels

Créer, entraîner et évaluer des modèles de deep learning (réseaux de neurones) avec TensorFlow

Savoir traiter des datasets (texte, image, numérique) et préparer des pipelines de données

Implémenter des réseaux de neurones convolutifs (CNN) et récurrents (RNN) pour des applications avancées

Déployer et exporter un modèle TensorFlow pour la production

Training program

Module 1Introduction à TensorFlow et au Machine Learning

Présentation de l'écosystème TensorFlow, installation, premiers scripts. Concepts clés du machine learning supervisé et non supervisé. Exécution sur CPU et GPU. Présentation des tensors, opérations de bases, flux de calcul. Exercices d’initiation.

Module 2Création et Entraînement de Modèles Neuronaux

Programmation de modèles séquentiels et fonctionnels avec Keras. Construction d’un modèle de classification d’images sur MNIST. Préparation et prétraitement des données. Gestion de l’overfitting, validation croisée, early stopping. Visualisation avec TensorBoard. Exercices pratiques approfondis.

Module 3Applications Avancées et Déploiement

Implémentation de réseaux convolutifs (CNN) pour la vision, introduction aux réseaux récurrents (RNN), gestion de séquences et datasets textuels, word embeddings. Exportation, sauvegarde et conversion de modèles TensorFlow pour mobile/web. Notions de déploiement en production sur cloud/serveur. Bilan, QCM final, coaching de projet personnel.