Data science courses

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

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.

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

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

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

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

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

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

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

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

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

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

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

Analyze text data in R using the tidy framework.

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

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

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

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

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

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.

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

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

Master sampling to get more accurate statistics with less data.

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

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

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

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

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

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

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