Courses

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

The successful implementation of AI solutions in clinical practice requires teams that are skilled in multiple disciplines, including data science, user-centered design, subject-matter expertise, change management, and more. However, the health care field

Discover how artificial intelligence is transforming today's businesses and how you can leverage it to grow your company into an AI-first leader.

Leading Successful Programs will challenge you to rethink your programs' goals and reassess how you gather, evaluate, and use data to determine their effectiveness.

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

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.

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

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

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

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.

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

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

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

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

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.

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

Increase your quantitative reasoning skills through a deeper understanding of probability and statistics, with the engaging “Fat Chance” approach that’s made this course a favorite among learners worldwide.

Lead the strategic response to cyber risk.

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

Learn about advances in interpretation of medical images using deep learning systems that can aid in clinical screening and diagnosis.

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.

Explore the risks and rewards of data privacy and collection.

Think critically about social questions such as education policy, upward income mobility, and racial disparities, and understand how big data can answer these questions as well as impact policies that lead to improved outcomes around the world.

In partnership with the Disparities Solutions Center at Massachusetts General Hospital, this course will help you deliver high-quality health care to all through organizational change.

Learn how to protect your own data, devices, and systems from today's threats.

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.

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

A gentle introduction to programming that prepares you for subsequent courses in coding.

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