Develop skills in digital research and visualization techniques across subjects and fields within the humanities.

Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal...

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.

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

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.

Learn skills and tools that support data science and reproducible research, to ensure you can trust your own research results,...

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.

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.