Courses

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.

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

Apply tools of single-variable calculus to create and analyze mathematical models used by real practitioners in social, life, and physical sciences.

Combine literary research with data science to find answers in unexpected ways. Learn basic coding tools to help save time and draw insights from thousands of digital documents at once.

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 about advances in interpreting biomedical signals and the use of machine learning and deep learning to aid in analysis and diagnosis.

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

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

Dive into the mechanisms of action and exciting applications of new FDA-approved genetic medicines.

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

Learn how to create, read, update, and delete data with relational databases.