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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 de Stable-Baselines3, vos implémentations d'apprentissage par renforcement en Python génèrent des bugs récurrents et des agents sous-performants, freinant tout projet IA.
Une équipe perd en moyenne 30% de temps de développement et 45 000 € en ressources GPU par projet RL mal optimisé, selon des benchmarks industry.
75% des échecs en RL professionnels sont liés à une mauvaise utilisation de ces outils, exposant l'entreprise à une perte de compétitivité et risquant des licenciements pour les data scientists.
Chaque trimestre sans ces compétences critiques creuse l'écart avec les leaders IA, menaçant la survie business.
The Maîtriser Stable-Baselines3 : Implémenter l’Apprentissage par Renforcement 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 Stable-Baselines3 : Implémenter l’Apprentissage par Renforcement 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 Stable-Baselines3 : Implémenter l’Apprentissage par Renforcement 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.
Concepts fondamentaux du RL (agent, environnement, récompense). Présentation de Stable-Baselines3 et de la bibliothèque Gym. Installation de l’environnement Python adapté (envs, dépendances, CUDA si GPU). Implémentation d’un agent simple sur CartPole. Exercices dirigés.
Présentation détaillée des algorithmes principaux de Stable-Baselines3 (DQN, PPO, A2C). Choix d’algorithme en fonction des cas d’usage. Paramétrage des environnements et gestion des seeds pour la reproductibilité. Suivi des logs et visualisation des résultats. Test de robustesse sur différents environnements (Atari, classiques, personnalisés).
Optimisation des hyperparamètres, gestion de la persistance des modèles, sauvegarde et reprise d'entraînement. Intégration avec Tensorboard et analyse avancée des résultats. Exportation de modèles RL pour la production ou la recherche. Étude de cas guidé sur un environnement personnalisé (OpenAI Gym ou votre propre application). Conseils pour poursuivre en autonomie, ressources et communauté.
Target audience
Développeurs Python, Data Scientists, chercheurs en IA souhaitant explorer ou approfondir l'apprentissage par renforcement avec Stable-Baselines3
Prerequisites
Connaissance des bases de Python. Notions en machine learning recommandées.
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