{"id":7286,"date":"2020-10-27T19:09:02","date_gmt":"2020-10-27T19:09:02","guid":{"rendered":"https:\/\/eiaschum.ca\/?post_type=product&p=7286"},"modified":"2020-10-29T13:22:18","modified_gmt":"2020-10-29T13:22:18","slug":"fondamentaux-pour-le-big-data","status":"publish","type":"product","link":"https:\/\/eiaschum.ca\/en\/produit\/fondamentaux-pour-le-big-data\/","title":{"rendered":"Fondamentaux pour le Big Data"},"content":{"rendered":"

Le MOOC \u00ab\u2009Fondamentaux pour le big data\u2009\u00bb permet d\u2019acqu\u00e9rir efficacement le niveau pr\u00e9requis en informatique et en statistiques pour suivre des formations dans le domaine du big data et data science.<\/p>\n

Le big data offre de nouvelles opportunit\u00e9s d\u2019emplois au sein des entreprises et des administrations. De nombreuses formations pr\u00e9parant \u00e0 ces opportunit\u00e9s de m\u00e9tiers existent. Le suivi de ces formations n\u00e9cessite des connaissances de base en statistiques et en informatique que ce MOOC vous propose d\u2019acqu\u00e9rir dans les domaines de l\u2019analyse, alg\u00e8bre, probabilit\u00e9s, statistiques, programmation Python et bases de donn\u00e9es.<\/p>\n

D\u2019une part, les bases de donn\u00e9es relationnelles ne sont pas toujours adapt\u00e9es aux syst\u00e8mes de donn\u00e9es massives qui sont d\u00e9ploy\u00e9es dans les contextes big data\u2009; ce MOOC vous explique pourquoi.<\/p>\n

D\u2019autre part, le langage Python est un langage tr\u00e8s utilis\u00e9 dans le domaine du traitement des masses de donn\u00e9es. Ce cours vous initie \u00e0 la programmation avec ce langage, particuli\u00e8rement en utilisant la biblioth\u00e8que Numpy.<\/p>\n

Enfin, le traitement des donn\u00e9es massives et la pr\u00e9diction n\u00e9cessitent des analyses statistiques. Cette formation vous fournit les concepts \u00e9l\u00e9mentaires en statistiques tels que les variables al\u00e9atoires, le calcul diff\u00e9rentiel, les fonctions convexes, les probl\u00e8mes d\u2019optimisation et les mod\u00e8les de r\u00e9gression. Ces bases sont appliqu\u00e9es sur un algorithme de classification le Perceptron.<\/p>\n

https:\/\/www.fun-mooc.fr\/courses\/course-v1:MinesTelecom+04006+session10\/about<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Dur\u00e9e<\/a>\u00a0: Plus de 6 heures
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