General 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.

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.

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

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

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

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.

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

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.

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

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

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.

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

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

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

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.

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.

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.

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 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.

Explore the risks and rewards of data privacy and collection.

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

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

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