Data Science Courses

Explore the risks and rewards of data privacy and collection.

Master how to use AI in your everyday work and drive impact at your organization. Access on-demand learning modules, expert-led sessions, and Harvard insights that help you apply AI to real business challenges—join today for access through September 2026.

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

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

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.

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

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.

An on-campus program to help architects, designers, workplace professionals, and people experts design their workplace for 2024 and beyond.

Learn how to use R to implement linear regression, one of the most common statistical modeling approaches in data science.

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

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

This three-course program from Harvard Business School (HBS) Online will teach you the fundamental skills to confidently contribute to business decisions and decision-making.  

Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.

Learn to process and convert raw data into formats needed for analysis.  

Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.

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

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

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

Sentar las bases de conocimiento en R y aprender a discutir, analizar y visualizar datos.

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

Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.

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

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

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

Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.

Learn to process and convert raw data into formats needed for analysis.  

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

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.

Develop a data mindset and the analytical skills to interpret and communicate data while applying concepts to real business problems in this course from Harvard Business School (HBS) Online.