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...

Data Visualization with ggplot2 (Part 1) Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

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

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

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 Shell for Data Science The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs ...

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

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

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

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.

Cluster Analysis in R Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract in...

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

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

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.

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.

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

Building Web Applications in R with Shiny: Case Studies Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

Single-Cell RNA-Seq Workflows in R Analyze single-cell RNA-Seq data using normalization, dimensionality reduction, clustering and differential expression.

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...

Forecasting Product Demand in R Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of pr...

Introduction to Bioconductor Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!

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...

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: Correlation and Linear R... If you have ever taken a math or statistics class, youâ€™ve probably heard the old adage "Correlation does not imply ca...

Education Data Analysis Primer: R, dplyr and Plotly This tutorial is designed to give an introduction to working with student data. R and dplyr will be used to reshape t...