Courses

Traces Albert Einstein’s engagement with relativity, quantum mechanics, Nazism, nuclear weapons, philosophy, the arts, and technology.

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

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

A quantitative introduction to the energy system and its environmental impacts.

Learn the anatomy basic to understanding five musculoskeletal injuries commonly seen in primary care medicine and orthopedic clinical specialty practice. Follow hypothetical patients from injury to operating room.

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 global warming impacts human health, and the ways we can diminish those impacts.

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

Discover how neurons work together to create complex networks inside the brain.

HKS Executive Education and Harvard's John A. Paulson School of Engineering and Applied Sciences present a webinar featuring Harvard faculty Martin Wattenberg and Fernanda Viégas.

A human-centered approach to the fundamentals of cell biology with a focus on the power plants of the cell - mitochondria.

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 to forecast the weather just by looking out your window.

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

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

Learn how electricity makes the neurons in your brain tick.

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.

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

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.

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

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

An introduction to the study of bioethics and the application of legal and ethical reasoning.

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

Learn about public policy in America and the dynamics of American politics.

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

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