General Courses

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

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

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic 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.

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

The structure, annotation, normalization, and interpretation of genome scale assays.

Designed for aspiring and established leaders in any industry, HBAP equips participants with the machine learning and data analysis tools they need to incorporate innovative tech into their business strategy, at the top levels of their organization.

Data Science Principles is a Harvard Online course in collaboration with Harvard Business School Online that provides an overview of data science with a code- and math-free introduction to prediction, causality, data wrangling, privacy, and ethics.

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 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.

Explore the risks and rewards of data privacy and collection.

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.