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Tutoriels sur la science des données

Faites progresser votre carrière dans le domaine des données grâce à nos tutoriels sur la science des données. Nous vous guidons pas à pas à travers les fonctions et les modèles de science des données les plus complexes.
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Bootstrap in R Tutorial

In this tutorial, you will learn how to use the boot package to obtain different types of bootstrapped confidence intervals.

Łukasz Deryło

9 octobre 2018

Subsetting Datasets in R

Subsetting datasets is a crucial skill for any data professional. Learn and practice subsetting data in this quick interactive tutorial!
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Tom Jeon

8 octobre 2018

Contingency Analysis using R

In this tutorial, you'll learn with the help of an example how "Contingency Analysis" or "Chi-square test of independence" works and also how efficiently we can perform it using R.
Vedabrata Basu's photo

Vedabrata Basu

5 octobre 2018

Demystifying Crucial Statistics in Python

Learn about the basic statistics required for Data Science and Machine Learning in Python.
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Sayak Paul

27 septembre 2018

Factor Levels in R

This tutorial takes course material from DataCamp's free Intro to R course and allows you to practice Factors.
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Ryan Sheehy

27 septembre 2018

Creating a List in R

Practice Lists in R by using course material from DataCamp's Intro to R course.
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Ryan Sheehy

27 septembre 2018

Introduction to Customer Segmentation in Python

In this tutorial, you're going to learn how to implement customer segmentation using RFM(Recency, Frequency, Monetary) analysis from scratch in Python.
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Avinash Navlani

26 septembre 2018

For Loops in R

When you know how many times you want to repeat an action, a for loop is a good option. Master for loops with this tutorial.
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Ryan Sheehy

26 septembre 2018

Joining DataFrames in pandas: merge(), concat() & join()

Learn how to join and merge DataFrames in pandas using concat(), merge(), and join() with practical examples.
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DataCamp Team

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Abid Ali Awan

5 février 2026

Lists: N-Sized Chunks

In this tutorial, you shall work with lists and learn an efficient way to divide arbitrarily sized lists into chunks of a given size.
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Sejal Jaiswal

12 septembre 2018