## Introduction to R

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

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129 results ## Introduction to R

## Introduction to the Tidyverse

## Intermediate R

## Data Manipulation with dplyr

## Introduction to Data Visualization with ggplot2

## Introduction to Statistics in R

## Introduction to Importing Data in R

## Exploratory Data Analysis in R

## Introduction to Regression in R

## Joining Data with dplyr

## Intermediate Data Visualization with ggplot2

## Intermediate Regression in R

## Supervised Learning in R: Classification

## Reporting with R Markdown

## Introduction to R for Finance

## Unsupervised Learning in R

## Reshaping Data with tidyr

## Supervised Learning in R: Regression

## Modeling with tidymodels in R

## Hypothesis Testing in R

## Communicating with Data in the Tidyverse

## Introduction to Writing Functions in R

## Cleaning Data in R

## Interactive Data Visualization with plotly in R

## Building Web Applications with Shiny in R

## Foundations of Probability in R

## Writing Efficient R Code

## Sampling in R

## Web Scraping in R

## Introduction to Text Analysis in R

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

4 hoursProgrammingJonathan Cornelissencourses

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

4 hoursProgrammingDavid Robinsoncourses

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

6 hoursProgrammingFilip Schouwenaarscourses

Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.

4 hoursData ManipulationJames Chapmancourses

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

4 hoursData VisualizationRick Scavettacourses

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

4 hoursProbability & StatisticsMaggie Matsuicourses

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

3 hoursData PreparationFilip Schouwenaarscourses

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

4 hoursExploratory Data AnalysisAndrew Braycourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursData ManipulationDataCamp Content Creatorcourses

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

4 hoursData VisualizationRick Scavettacourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

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

4 hoursMachine LearningBrett Lantzcourses

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

4 hoursReportingAmy Petersoncourses

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

4 hoursApplied FinanceLore Dirickcourses

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

4 hoursMachine LearningHank Roarkcourses

Transform almost any dataset into a tidy format to make analysis easier.

4 hoursData ManipulationJeroen Boeyecourses

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

4 hoursMachine LearningJohn Mountcourses

Learn to streamline your machine learning workflows with tidymodels.

4 hoursMachine LearningDavid Svancercourses

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

4 hoursProbability & StatisticsRichie Cottoncourses

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

4 hoursData VisualizationTimo Grossenbachercourses

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

4 hoursProgrammingRichie Cottoncourses

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

4 hoursData PreparationMaggie Matsuicourses

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

4 hoursData VisualizationAdam Loycourses

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

4 hoursProgrammingkaelen medeiroscourses

In this course, you'll learn about the concepts of random variables, distributions, and conditioning.

4 hoursProbability & StatisticsDavid Robinsoncourses

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

4 hoursProgrammingColin Gillespiecourses

Master sampling to get more accurate statistics with less data.

4 hoursProbability & StatisticsRichie Cottoncourses

Learn how to efficiently collect and download data from any website using R.

4 hoursData PreparationTimo Grossenbachercourses

Analyze text data in R using the tidy framework.

4 hoursData ManipulationMaham Khancourses