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Avis et commentaires pour d'étudiants pour Processing Data with Python par Coursera Project Network

198 évaluations
29 avis

À propos du cours

Processing data is used in virtually every field these days. It is used for analyzing web traffic to determine personal preferences, gathering scientific data for biological analysis, analyzing weather patterns, business practices, and on. Data can take on many different forms and come from many different sources. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. It has libraries that can be used to parse and quickly analyze the data in whatever form it comes in, whether it be in XML, CSV, or JSON format. Data cleaning is an important aspect of processing data, particularly in the field of data science. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Meilleurs avis


25 sept. 2020

Instructor Explains very well in the programming part and as well as project guidance thank you Coursera for offering such a wonderful Lectures and project tutorials Thank you once again


17 août 2020

Great project to begin understanding data processing in python

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26 - 29 sur 29 Avis pour Processing Data with Python

par steven f

23 juil. 2020

The web platform used is difficult to navigate.

par Mohammad D A

13 juin 2020

It could have been more interesting.

par Bruce B

28 nov. 2021

This is a basic course at best and should not be branded intermediate. I took this course hoping to gain experience in real-world data cleaning and manipulation. The toy dataset and techniques demonstrated were basic and would not go far in a real-world application. Don't do it unless you are an absolute beginner, and even then, there are better courses out there.

par Mirosław J

21 juin 2021

A​nother "type read_csv to read csv file"-style course, where nothing is explained. Do not recommend.