Data Analysis Courses

Learn how to use decision trees, the foundational algorithm for your understanding of machine learning and artificial intelligence.

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

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

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

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

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

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.

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.

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

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

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