Data Science Courses

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.

Build practical deep learning skills for Python-savvy professionals.

Build a foundational understanding of AI concepts with this course from Harvard Business School (HBS) Online.

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

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

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

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

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

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

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

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

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

Join Harvard University instructor Pavlos Protopapas in this online course to learn how to use Python to harness and analyze data.

Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, you’ll be implementing an entire TinyML application.

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

Join Harvard University instructor Pavlos Protopapas in this online course to learn how to use Python to harness and analyze data.

This Harvard Medical School one-year, application-based certificate program helps leaders effect positive change by learning to turn patient data into actionable, transformable knowledge.

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

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

Build practical skills that will prepare you to interpret data, test ideas, and apply predictive and AI insights to real-world business decisions in this course from Harvard Business School (HBS) Online.

Data Science and AI Principles is a Harvard Online course that gives you an overview of data science and AI systems with a nearly code- and math-free introduction to prediction, causality, visualization, data wrangling, privacy, ethics.

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

Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio.

Data Science and AI Principles is a Harvard Online course that gives you an overview of data science and AI systems with a nearly code- and math-free introduction to prediction, causality, visualization, data wrangling, privacy, ethics.

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

An on-campus program to help architects, designers, workplace professionals, and people experts design their workplace for 2026 and beyond.

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

This course from Harvard Business School (HBS) Online will teach you the practical skills to turn data insights into strategic action.

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.