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.

Explore the risks and rewards of data privacy and collection.

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.

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

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

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

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.  

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

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

Build practical deep learning skills for Python-savvy professionals.

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

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

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

Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.

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

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

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

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

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.

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

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.

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

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

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

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

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 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.