Learn basic data visualization principles and how to apply them using ggplot2.

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008.

Learn inference and modeling: two of the most widely used statistical tools in data analysis.

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.

Learn to process and convert raw data into formats needed for analysis. 

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

Show what you’ve learned from the Professional Certificate Program in Data Science.

Build a foundation in R and learn how to wrangle, analyze, and visualize data.

A focus on several techniques that are widely used in the analysis of high-dimensional data.

A focus on the techniques commonly used to perform statistical inference on high throughput data.

Learn to use R programming to apply linear models to analyze data in life sciences.

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences.

Designed for aspiring and established leaders in any industry, The Harvard Business Analytics Program helps students not just...

Designed for aspiring and established leaders in any industry, The Harvard Business Analytics Program helps students not just...