Data Analysis Courses

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.

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.

Taught by a real estate economist and data expert, you will learn to use technology, proprietary data, and a proven framework to elevate your decision making and real estate investment outcomes.

Learn introductory programming and data analysis in MATLAB, with applications to biology and medicine.

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

Designed for aspiring and established leaders in any industry, The Harvard Business Analytics Program helps students not just analyze data but understand it, translate it, and incorporate it into strategy at the top levels of their organizations.

Learn how to effectively use data to tackle your business decisions. Designed for managers, this course provides a hands-on approach for demystifying the data science ecosystem and making you a more conscientious consumer of information.

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

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 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.