Key Courses - DrPH in Applied AI and Data Translation
The DrPH is a fully online, 60 credit-hour program that can be completed full-time (8-11 credit hours per semester) or part-time (5-7 credit hours per semester) in three to seven years.
Electives
In addition to the courses below, students will choose electives to align further training with their unique interests (e.g., application of implementation and evaluation science or preparedness and response in the context of global health, environmental health, behavioral/social science etc.).
A minimum of 9 credit hours at the master's (500) or doctoral (700) level are required.
Foundational Curriculum
The foundational curriculum consists of 25 credit hours of coursework which all students, regardless of their selected concentration, must complete.
The DrPH foundational curriculum also includes the following courses:
- DRPH 717: Health Equity through Action on the Social Determinants of Health
- DRPH 718: Integrating Law, Ethics, and Politics into Public Health Policy
- DRPH 719: Curriculum Development for the Public Health Workforce
Online Asynchronous. PRE-REQ: DrPH Only. This course focuses on the development of a community intervention or program designed to address a public health issue. Students will select a public health challenge and develop a system-level program plan that takes into account cultural value and practices.
Online Asynchronous. PRE-REQ: DrPH Only. This course teaches principles and methods of public health surveillance and its implications in public health practice. It concentrates on skill development in areas including the establishment of a public health surveillance program, the collation and analysis of data, data implications, program evaluation research, preparation and distribution of a surveillance report. The course also helps students recognize the importance of a direct association between a public health surveillance program and a public health action.
Online Asynchronous. PRE-REQ: DrPH Only. This course is designed to introduce students to the mixed methods paradigm in public health research and evaluation practice. The core goal of the course is to blend theory and practice in designing and conducting mixed methods research and evaluation. Students will learn the science behind developing rigorous mixed methods research, including: developing aims, determining the study design and sampling plan, constructing data collection instruments, communicating study findings, and assessing reliability, validity, and ethical issues in mixed methods studies. Ultimately, students will learn to communicate about the importance of using multiple methods of data collection to enhance translation of research and evaluation findings into improving public health practice.
Online Asynchronous. PRE-REQ: DrPH Only. Promoting health (both individual and at the population level) is inherently an interprofessional activity that requires strong leadership skills as well as integration of knowledge and methods across professions and sectors. As a health professional you will interact with experts from multiple fields, including medical doctors, nurses, public health professionals, lawyers, and educators. Communicating with individuals from other professions, even when working toward a common goal, can be challenging. This course will help you assess your leadership capacities and cultural proficiency and to enhance your performance effectively in interprofessional teams.
Online Asynchronous. PRE-REQ: DrPH Only. This course explores methods of applying behavioral and cognitive theories for effectively communicating health and behavioral change information and maximizing compliance with public health guidelines. It illustrates communication strategies using a variety of approaches including face-to-face instruction, technology-based strategies, electronic media, print-based products and adds media engagement. This course also provides students with an overview of concepts and strategies used in data presentation, social marketing, and public health information campaigns. Emphasis is placed on developing skills that enable practitioners to create and gain compliance with consumer-oriented public health interventions, advocacy strategies, and professional development initiatives. Skills covered in this course include formative research, audience segmentation, communication channel analysis, and multidimensional data presentation.
Online Asynchronous. PRE-REQ: DrPH Only. This course examines the formulation and implementation of business strategies in health care organizations, models of strategic management, and the role of stakeholders in the strategic management process. Reviews specific analytical tools used in strategy formulation, choice, and implementation, with an emphasis on real-world health care applications. Demonstrates how to use analysis tools to develop a comprehensive strategic implementation plan. Investigates when internal funding can and should be used as part of implementation and when and how to pursue external funding.
Online Asynchronous. PRE-REQ: DrPH Only. Negotiation is a critical element of everyday life in an organization and personal relations. How much will I earn in my job? How should I deal with a dissatisfied customer? How do my co-workers and I decide how we will manage a project? These are all examples of common work situations where we find ourselves negotiating with others. Yet, many know little about the strategies and conditions that lead to the most effective negotiated outcomes. The purpose of this course is to understand the basic theory and processes of negotiation so that you can negotiate successfully in a variety of organizational settings. Students will actively develop these skills by preparing for and simulating a variety of negotiations.
Concentration Curriculum
In addition to the foundational curriculum, students will complete 12 credit hours of coursework within their concentration.
The applied AI and data science curriculum also includes the following courses:
- DRPH 742: Data Governance, Ethics, and Privacy in Public Health
- DRPH 743: Case Studies in Applied Data-Driven Public Health Strategies
Online Asynchronous. PRE-REQ: DrPH AIDT Track Only. This course provides an overview of data-driven machine learning and AI methods and their real-world applications in public health, with emphasis on practical and hands-on learning. The topics covered in this course include supervised and unsupervised machine learning methods and their implementation using open-source libraries in R or Python programming languages. Students will learn about the stages of the AI development lifecycle from training, validation to deployment, and develop skills to apply AI techniques to large-scale public health datasets and draw insights to support data-driven decision making.
Online Asynchronous. Prerequisites: DrPH AIDT Track Only. This course provides an overview of data analysis and visualization techniques to communicate public health data insights via graphs, charts, maps, and dashboards. The core goal of the course is to help students on how to use data visualizations to analyze public health data (e.g., biomarkers, epidemiological data, sensors data, surveillance data, and electronic health records), present complex data in a meaningful way and communicate data insights in an impactful way to diverse audiences. Students will learn key concepts and gain hands-on working knowledge by designing and implementing advanced data visualizations and critiquing public health visualizations.