Wolf Riepl

Introduction to Python

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

Introduction to R

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

Intermediate Python for Data Science

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Introduction to the Tidyverse

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

Intermediate R

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

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.

Cleaning Data in R

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

Data Manipulation in R with dplyr

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

Introduction to Data in R

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

Supervised Learning in R: Classification

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

Correlation and Regression in R

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

Writing Functions in R

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

Exploratory Data Analysis in R

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

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.

Introduction to Git for Data Science

This course is an introduction to version control with Git for data scientists.

Reporting with R Markdown

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

Introduction to Machine Learning

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

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.

Data Visualization with ggplot2 (Part 2)

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

Unsupervised Learning in R

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

Joining Data in R with dplyr

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

Multiple and Logistic Regression in R

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

Building Web Applications in R with Shiny

Build interactive web apps straight from R with shiny!

Time Series Analysis in R

Learn the core techniques necessary to extract meaningful insights from time series data.

Machine Learning Toolbox

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

Data Visualization in R

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

Exploratory Data Analysis in R: Case Study

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

Supervised Learning in R: Regression

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

Working with Data in the Tidyverse

Learn to work with data using tools from the tidyverse, and master the important skills of taming and tidying your data.

Writing Efficient R Code

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

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.

Intermediate R: Practice

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

Working with the RStudio IDE (Part 1)

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

Foundations of Probability in R

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

Working with Dates and Times in R

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

Building Web Applications in R with Shiny: Case Studies

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

Parallel Programming in R

This course covers in detail the tools available in R for parallel computing.

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 in R

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

Modeling with Data in the Tidyverse

Explore Linear Regression in a tidy framework.

Manipulating Time Series Data in R with xts & zoo

The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.

Interactive Maps with leaflet in R

Learn how to produce interactive web maps with ease using leaflet.

Building Dashboards with shinydashboard

In this course you'll learn to build dashboards using the shinydashboard package.

Machine Learning with Tree-Based Models in R

In this course, you'll learn how to use tree-based models and ensembles for regression and classification.

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.

Text Mining: Bag of Words

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

ARIMA Modeling with R

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Communicating with Data in the Tidyverse

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

Visualization Best Practices in R

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and percep...

Generalized Linear Models in R

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

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 ...

Working with the RStudio IDE (Part 2)

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

Introduction to Spark in R using sparklyr

Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.

Visualizing Time Series Data in R

Learn how to visualize time series in R, then practice with a stock-picking case study.

Hierarchical and Mixed Effects Models in R

In this course you will learn to fit hierarchical models with random effects.

Data Visualization with ggplot2 (Part 3)

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

Categorical Data in the Tidyverse

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey respons...

Data Visualization in R with ggvis

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

Building Dashboards with flexdashboard

In this course you'll learn how to create static and interactive dashboards using flexdashboard and shiny.

Linear Algebra for Data Science in R

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data sci...

Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Object-Oriented Programming in R: S3 and R6

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

Foundations of Functional Programming with purrr

Learn to easily summarize and manipulate lists using the purrr package.

Intermediate Functional Programming with purrr

Continue learning with purrr to create robust, clean, and easy to maintain iterative code.

Nonlinear Modeling in R with GAMs

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science ...

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...

Developing R Packages

Create and share your own R Packages!

Scalable Data Processing in R

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

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.

Data Visualization in R with lattice

Learn to visualize multivariate datasets using lattice graphics.

Defensive R Programming

Learn defensive programming in R to make your code more robust.

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...