Harvard T.H. Chan School of Public Health

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

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

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

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

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

Protecting the public from harm during a radiological event requires a thorough and well-designed radiological emergency management program.

Take your introductory knowledge of Python programming to the next level and learn how to use Python 3 for your research.

This self-paced leadership development program equips mid-level nurse managers with essential skills in performance management, negotiation, health care technology, resource management, quality improvement, and more. Start any time.

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

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

Learn how to protect children from violence, exploitation, and neglect through law, policy, and practice in a human rights framework.

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

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.

This program brings together physicians in administrative positions in academic health centers, report directly to the chair of their department, to study the critical leadership and management issues facing academic health centers.

How can we eradicate malaria? Explore cutting-edge science and technology, and examine policies needed, to control and eliminate malaria.

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

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

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

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

Understanding the context for the Ebola outbreak: What went right, what went wrong, and how we can all do better.

The importance of reducing the mental health care gap has never been more critical. The current reality of limited financial resources, stigma associated with mental health problems, and too few professionals to support the vast mental health needs of the

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

Learn the principles guiding humanitarian response to modern emergencies, and the challenges faced in the field today.

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

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

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

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

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

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

Learn how a Culture of Health can transform your business by integrating worker, customer, community, and environmental well-being for sustainable success.