Courses Details

HMP628: Data Analytics in Healthcare

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 Credit Hour(s) for residential students;
  • Instructor(s): McCullough, Jeffrey (Residential);
  • Not offered 2020-2021
  • Prerequisites: None
  • Advisory Prerequisites: A basic understanding of machine learning and 'R' would be useful
  • Description: This course will introduce students to machine learning and other big data analytic techniques. We will illustrate the strengths and limitations of these tools and their applications for policy and industry. Topics will include risk prediction, precision medicine, and population health. We will also discuss the legal and ethical issues.
  • Learning Objectives: 3. Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population's health. 10. Explain the social, political and economic determinants of health and how they contribute to population health and health inequities.