About this Program

Big data is the new norm across health industries. Health organizations, insurance companies and government agencies increasingly rely on experts who have formal training in data science to discover powerful insights and make informed decisions.

In this three-course certificate program, you’ll take a comprehensive look at data science concepts — including statistics and machine learning — and how they apply in the context of health economics and outcomes research (HEOR). Without delving into coding or complex statistical derivations, you’ll learn to employ these fundamental concepts for health care data analysis and decision-making. You’ll take away knowledge you can use to evaluate data science projects and make evidence-based decisions that advance health research, policy and outcomes.

Designed For

Professionals who want to understand how big data is used to make decisions in health and policy settings, including payer organizations, health industries, and government agencies, as well as life sciences, pharmaceutical and biomedical industries.

See Requirements

What You’ll Learn

• Methods to critically evaluate data science projects, sources and health care data comparisons
• Strategies for working with big data in real-world systems, including claims and electronic health records
• Introductory statistics concepts, including causal inference methods and how to choose among covariates
• Concepts about machine learning methods and applications in HEOR

Get Hands-On Experience

Each quarter, you’ll complete an individual capstone project related to data science in health economics and outcomes research.

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