Wolf Riepl

Introduction to Python

Master the basics of data analysis in Python. Expand your skill set 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 data frames with Pandas.

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...

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.

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.

Introduction to Git for Data Science

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

Communicating with Data in the Tidyverse

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

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

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.

Writing Functions in R

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

Introduction to Machine Learning

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

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.

Reporting with R Markdown

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

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.

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.

Machine Learning Toolbox

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

Joining Data in R with dplyr

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

Visualization Best Practices in R

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

Building Web Applications in R with Shiny

Build interactive web apps straight from R with shiny!

Multiple and Logistic Regression

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

Foundations of Probability in R

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

Exploratory Data Analysis in R: Case Study

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

Writing Efficient R Code

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

Building Web Applications in R with Shiny: Case Studies

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

Introduction to Time Series Analysis

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

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.

Supervised Learning in R: Classification

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

Working with the RStudio IDE (Part 1)

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

Unsupervised Learning in R

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

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.

Modeling with Data in the Tidyverse

Explore Linear Regression in a tidy framework.

Intermediate R: Practice

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

String Manipulation in R with stringr

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

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.

Supervised Learning in R: Regression

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

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.

ARIMA Modeling with R

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

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.

Introduction to Spark in R using sparklyr

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

Foundations of Inference

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

Hierarchical and Mixed Effects Models

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

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

Parallel Programming in R

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

Generalized Linear Models in R

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

Building Dashboards with flexdashboard

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

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...

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...

Visualizing Time Series Data in R

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

Object-Oriented Programming in R: S3 and R6

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

Data Visualization in R with ggvis

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

Foundations of Functional Programming with purrr

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

Data Visualization with ggplot2 (Part 3)

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

Working with Dates and Times in R

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

Interactive Maps with leaflet in R

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

Intermediate Functional Programming with purrr

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

Developing R Packages

Create and share your own R Packages!

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...

Support Vector Machines in R

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

Data Visualization in R with lattice

Learn to visualize multivariate datasets using lattice graphics.

Nonlinear Modeling in R with GAMs

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

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.

Scalable Data Processing in R

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

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...