Les destinataires de ce cours : This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. Only minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.

Créé par :   University of Michigan

Informations de base
Comment réussirRéussissez tous les devoirs notés pour terminer le cours.
Notes des utilisateurs
4.5 stars
Average User Rating 4.5Voir ce que disent les étudiants
Programme de cours

Comment cela fonctionne
Travail en cours
Travail en cours

Chaque cours fonctionne comme un manuel interactif en proposant des vidéos préenregistrées, des quiz et des projets.

Aide de la part de vos pairs
Aide de la part de vos pairs

Connectez-vous à des milliers d'autres étudiants et débattez sur des idées, discutez le contenu du cours et obtenez de l'aide pour en maîtriser les concepts.


Obtenez une reconnaissance officielle pour votre travail et partagez votre réussite avec vos amis, vos collègues et vos employeurs.

University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Notation et examens
Note moyenne 4.5 sur 5 sur 1,648 notes

Very informative. Would be interested to see the correct way to complete many of the assignments, as I'm sure there are more elegant ways to complete them than I used

Nice course for beginners

excellent course

Much harder than I thought. Very in-depth introductory learning of python.

Preferably better if you allow scripting in .py because notebook is rather heavy and hard to

debug while assignments..

Hope you cover a bit more in detail with language structure, as well as give hints for solving assignments, since many parts were pretty above course level.

I would say the assignments were hard even for an R practitioner learning python like myself.