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This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! Amandine Velt | Data Science - Python - R, Récupérer des données et les intégrer dans son environnement de travail, Connaitre les différentes structures de données (listes, dictionnaires, tableaux, dataframes, ...), Manipuler efficacement des données avec Python et la librairie Pandas, Explorer et visualiser des données avec Matplotlib et Seaborn, Utiliser Python pour faire de la data science, Installation de l'environnement de travail (Windows, Mac, Linux), Les bibliothèques Python essentielles à la Data Science, Prise en main du tableau de bord de Jupyter Notebook, Prise en main des notebooks de Jupyter Notebooks, Importer une bibliothèque et utiliser ses fonctions, Testez vos connaissance sur les bases de Python, Accéder aux éléments d'une liste (slicing), Ajouter/modifier/supprimer des éléments d'une liste, Diverses manipulations des listes (tri, somme, concaténation, ...), Introduction de l'exercice : manipuler la liste des prix de 58 maisons, Correction de l'exercice : manipuler la liste des prix de 58 maisons, Ajouter/modifier/supprimer des éléments d'un dictionnaire, Introduction : exercice sur les dictionnaires, Correction : exercice sur les dictionnaires, Accéder aux éléments d'un array (slicing), Exercice : manipuler un array de 20 maisons vendues en 2008 aux Etats-Unis, Correction : manipuler un array de 20 maisons vendues en 2008 aux Etats-Unis, Utilisation de la bibliothèque Pandas pour manipuler les données, Ajouter/supprimer des colonnes d'un dataframe, Filtrer un Dataframe selon des conditions, Grouper un Dataframe sur une ou plusieurs colonnes (groupby), Introduction de l'exercice : étudier le marché Android via le Google play store, Correction de l'exercice : étudier le marché Android via le Google play store, Utilisation de Matplotlib et Seaborn pour la visualisation de données, Importation et description des données de vente du Black Friday, Ajouter un titre principal et des labels aux axes, Changer les couleurs (et colorer selon certaines variables), Exercice : visualiser les données de vente d'un magasin le jour du Black Friday, Correction : visualiser les données d'un magasin le jour du Black Friday, Coupon : apprendre la Data Science avec R de A à Z, Mon livre aux éditions ENI : Python pour la Data Science, AWS Certified Solutions Architect - Associate, Les personnes souhaitant apprendre à programmer en Python, Les personnes souhaitant apprendre à faire de la Data Science avec Python, Les personnes intéressées par la Data Science en général. 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