Course Offerings
Explore designing and implementing information technologies to improve healthcare delivery, healthcare management, and health outcomes. Offered on the letter-grade basis only.
Overview of public health and the information systems used to achieve public health goals. This course is divided into three parts: (1) overview of public health, (2) fundamentals of public health informatics, and (3) public health information systems.
Leveraging medical claims data to guide population health interventions, primarily through the use of machine learning models. The course will focus on the data processing pipeline, and no prerequisite knowledge of machine learning models is required
Explore principles and methodologies in health informatics research, including various approaches to data analysis, research design, and the application of informatics to health. Develop skills in reading, reviewing, and writing scientific publications, identifying research questions, initiating research, and communicating findings.
The course is designed for undergraduate students who are interested in understanding, analyzing, designing, evaluating, or developing technologies to serve the health needs of general consumers. It covers the concept of consumer health informatics, health behavior theories, health information seeking and information retrieval, various forms of consumer health systems, and the design and evaluation of such systems.
New Topic for Spring 2025. Description pending submission by instructor, Steve Hershman. Also offered as Informatics 320D.
This course offers students in Information Science a comprehensive exploration into the theories, techniques, and tools of data visualization. It is designed to equip students with the skills to effectively communicate complex information visually, enabling data analysis and decision-making. Through a combination of lectures, hands-on projects, and case studies, students will learn how to design and implement effective and aesthetically appealing data visualizations for a variety of data types and audiences. Upon successful completion of this course, students will be able to: • Understand the principles and psychology of visual perception and how they influence data visualization. • Critically evaluate the effectiveness of different data visualization techniques for varying data types and user needs. • Master the use of leading data visualization tools and libraries such as D3.js, or Tableau. • Develop interactive dashboards and reports that effectively communicate findings to both technical and non-technical audiences. • Apply design principles to create visually appealing, accurate, and accessible data visualizations.