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.

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.

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

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

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

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.

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.

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

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

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

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.

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

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

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

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

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

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

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

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

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.

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

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

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.

Build a foundation in R and learn how to wrangle, analyze, and visualize 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.

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