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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 l'analyse de données IoT, vos objets connectés produisent des volumes massifs de données inexploitées, paralysant les prises de décision stratégiques.
Les entreprises perdent en moyenne 1,2 million d'euros par an en opportunités manquées et coûts de maintenance dus à des analyses défaillantes, selon des études Gartner.
75% des projets IoT échouent par manque d'expertise analytique, exposant votre équipe à des incidents sécuritaires critiques et votre carrière à l'obsolescence rapide.
Chaque mois sans compétences avancées, le risque de non-conformité RGPD grimpe de 25%, avec des amendes pouvant atteindre 4% du chiffre d'affaires.
The IoT Analytics : Maîtriser l’Analyse de Données pour Objets Connectés 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 IoT Analytics : Maîtriser l’Analyse de Données pour Objets Connectés 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 IoT Analytics : Maîtriser l’Analyse de Données pour Objets Connectés 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.
Panorama des architectures IoT, protocoles de communication (MQTT, CoAP…), typologie des capteurs, nature des données recueillies (séries temporelles, volumétrie, fréquences, bruit). Exigences et contraintes liées à la donnée IoT en termes de secours, sécurité et confidentialité. Introduction aux flux de données temps réel vs données batch.
Formats courants (JSON, CSV, Parquet…), bases de données adaptées (TimeSeries DB, NoSQL, Cloud), ingestion en flux (streaming), nettoyage et normalisation des données, gestion des données manquantes et bruitées. Utilisation de plateformes cloud (AWS IoT Analytics, Azure IoT Hub, Google IoT Core).
Exploration des analytics descriptives, prédictives et prescriptives : corrélation, détection d’anomalies, maintenance prédictive. Introduction au Machine Learning appliqué à l’IoT (classification, clustering, séries temporelles). Mise en pratique avec outils open-source (Python Pandas, Scikit-learn, Grafana, Power BI). Élaboration de tableaux de bord interactifs pour la restitution des résultats.
Target audience
Ingénieurs, data analysts, chefs de projet IoT, professionnels de l’IT souhaitant exploiter les données générées par les objets connectés
Prerequisites
Connaissances de base en réseaux et en analyse de données, expérience préalable en IoT souhaitable
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