Data Analysis with Python Project
Coursera
24 Cours
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Aperçu
Le cours « Data Analysis with Python Project » proposé par l'Université du Colorado à Boulder et disponible sur Coursera est un programme complet conçu pour autonomiser les étudiants en appliquant les connaissances et compétences acquises à travers cette spécialisation. Dans ce cours, les participants seront emmenés dans un voyage instructif partant du traitement des données brutes à la dérivation de connaissances et d'intelligence à travers diverses techniques d'analyse de données.
Les étudiants plongeront profondément dans des domaines fondamentaux et avancés de l'analyse de données, y compris l'apprentissage supervisé et non supervisé, la régression, le clustering, la réduction de dimension, les règles d'association et la détection d'anomalies. Le programme est structuré pour non seulement fournir des aperçus théoriques mais aussi une expérience pratique à travers des tutoriels, des exercices pratiques et un projet de fin d'études axé sur l'analyse de données réelles.
À la fin de ce cours complet, les participants pourront :
- Comprendre les concepts fondamentaux et avancés dans l'analyse de données à travers un large spectre de méthodologies telles que la régression, la classification et le clustering.
- Définir et aborder les projets d'analyse de données avec des stratégies appropriées pour atteindre leurs objectifs, en exploitant des algorithmes de classification comme les Plus Proches Voisins, les Arbres de Décision, SVM, Naive Bayes et la Régression Logistique pour la modélisation prédictive.
- Améliorer la performance des modèles en utilisant la validation croisée et des techniques d'ensemble et appliquer des algorithmes de régression pour la prédiction de résultats numériques.
- Découvrir les motifs sous-jacents dans les données en utilisant des techniques de clustering et simplifier la complexité des données à travers la réduction de dimension en utilisant PCA.
- Extraire des règles d'association dans des données transactionnelles avec des algorithmes comme Apriori et FPGrowth et identifier les anomalies en utilisant différentes méthodes de détection.
Les participants ayant terminé ce cours seront compétents en analyse de données, prêts à appliquer leur expertise nouvellement acquise à une multitude de projets et à prendre des décisions informées basées sur les données. Ce cours est classé dans les cours Python, les cours d'Analyse de Données, l'Apprentissage Supervisé et l'Apprentissage Non Supervisé, ce qui le rend parfait pour les individus cherchant à affiner leurs compétences en analyse de données.
Programme
Enseigné par
Étiquettes
Coursera
Coursera
1449 Cours
Coursera
Free Online Course (Audit)
English
18 hours
On-Demand
Intermediate
