"Maîtrisez les bases de l'analyse de données en R : vecteurs, listes, data frames, et pratiquez avec des jeux de données réels."

Poursuivez votre parcours pour devenir un ninja de R en vous familiarisant avec les instructions conditionnelles, les boucles et les fonctions vectorielles.

Commencez à explorer et à visualiser vos propres données avec tidyverse, une collection puissante et populaire d'outils de science des données au sein de R.

Build Tidyverse skills by learning how to transform and manipulate data with dplyr.

Analyze the relative popularity of programming languages over time based on Stack Overflow data.

Learn to combine data across multiple tables to answer more complex questions with dplyr.

Développez vos compétences statistiques et apprenez à collecter des données, à les analyser et à en tirer des conclusions précises.

Apprenez à produire de belles visualisations de données avec ggplot2 en comprenant la grammaire des graphiques.

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.

Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Take your R skills up a notch by learning to write efficient, reusable functions.

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

Learn to perform linear and logistic regression with multiple explanatory variables.

Master sampling to get more accurate statistics with less data.

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

In this course you'll learn about basic experimental design, a crucial part of any data analysis.

In this course you will learn the basics of machine learning for classification.

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.