Wolf Riepl

Introduction to R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.

Intro to Python for Data Science

Master the basics of data analysis in Python. Expand your skill set by learning scientific computing with numpy.

Intermediate R

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

Introduction to the Tidyverse

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collect...

Data Visualization with ggplot2 (Part 1)

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

Importing Data in R (Part 1)

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

Data Manipulation in R with dplyr

Master techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.

Reporting with R Markdown

Learn to create interactive analyses and automated reports with R Markdown.

Cleaning Data in R

Learn to explore your data so you can properly clean and prepare it for analysis.

Working with the RStudio IDE (Part 1)

Learn the basics of the important features of the RStudio IDE.

Introduction to Data

Learn the language of data, study types, sampling strategies, and experimental design.

Exploratory Data Analysis

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

Introduction to Machine Learning

Learn to train and assess models performing common machine learning tasks such as classification and clustering.

Writing Functions in R

Learn the fundamentals of writing functions in R so you can make your code more readable and automate repetitive tasks.

Importing Data in R (Part 2)

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Correlation and Regression

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Supervised Learning in R: Classification

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

Building Web Applications in R with Shiny

Build interactive web apps straight from R with shiny!

Data Analysis in R, the data.table Way

Master core concepts in data manipulation such as subsetting, updating, indexing and joining your data using data.table.

Importing & Cleaning Data in R: Case Studies

In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

Intermediate R - Practice

Strengthen your knowledge of the topics you learned in Intermediate R with a ton of new and fun exercises.

Joining Data in R with dplyr

This course will show you how to combine data sets with dplyr's two table verbs.

Exploratory Data Analysis in R: Case Study

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Data Visualization with ggplot2 (Part 2)

Take your data visualization skills to the next level with coordinates, facets, themes, and best practices in ggplot2.

Data Visualization in R

This course provides a comprehensive introduction to working with base graphics in R.

Text Mining: Bag of Words

Learn the bag of words technique for text mining with R.

Machine Learning Toolbox

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Unsupervised Learning in R

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

Statistical Modeling in R (Part 1)

This course was designed to get you up to speed with the most important and powerful methodologies in statistics.

Working with the RStudio IDE (Part 2)

Further your knowledge of RStudio and learn how to integrate Git, LaTeX, and Shiny

Foundations of Probability in R

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

Multiple and Logistic Regression

In this course you'll lear to add multiple variables to linear models and to use logistic regression for classification.

String Manipulation in R with stringr

Learn how to pull character strings apart, put them back together and use the stringr package.

Foundations of Inference

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Data Visualization in R with ggvis

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Writing Efficient R Code

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

Supervised Learning in R: Regression

In this course you will learn how to predict future events using linear regression, generalized additive models, rand...

Object-Oriented Programming in R: S3 and R6

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

R for SAS, SPSS and STATA Users

Learn to translate your knowledge of SAS, SPSS, or Stata into R using the same statistics techniques you're familiar ...

Data Visualization with ggplot2 (Part 3)

This course covers some advanced topics including strategies for handling large data sets and specialty plots.

Statistical Modeling in R (Part 2)

In this follow-up course, you will expand your stat modeling skills from part 1 and dive into more advanced concepts.

Importing Data Into R

Learn how to parse data in any format. Whether it's flat files, statistics software, databases, or web data, you'll h...

Data Visualization in R with lattice

Learn to visualize multivariate datasets using lattice graphics.

Data Analysis and Statistical Inference

This interactive DataCamp course complements the Coursera course Data Analysis and Statistical Inference by Mine Çeti...

Intro to Statistics with R: Introduction

A friendly introduction to fundamental concepts in statistics in R.

Intro to Statistics with R: Student's T-test

If you want to have a solid basic foundation in statistics, it is essential to understand the concepts and theories b...

Intro to Statistics with R: Analysis of Variance (AN...

Analysis of Variance (ANOVA) is probably one of the most popular and commonly used statistical procedures. In this co...

Intro to Statistics with R: Repeated measures ANOVA

This course focuses on within-groups comparisons and repeated measures design. With the help of a working memory trai...

Intro to Statistics with R: Correlation and Linear R...

If you have ever taken a math or statistics class, you’ve probably heard the old adage "Correlation does not imply ca...

Intro to Statistics with R: Multiple Regression

Multiple regression is a powerful statistical technique, and here you will discover why and how to use it. Part of th...

Intro to Statistics with R: Moderation and Mediation

Moderation and mediation sound alike, but in reality they are quite different. This course will get you acquainted wi...