Advanced Exploration and Visualization in Health

3 credits · Graduate Programs

Introduction of deeper tools, skills, and techniques for collecting, manipulating, visualizing, analyzing, and presenting a number of different common types of data in the context of health and biostatistics. Techniques for visualizing and supporting interactive analysis and decision making for a variety of different types of data, including text, networks, and geographic, and temporal datasets will be introduced. There will be a focus on critical thinking, problem-solving, and good analysis practices to avoid cognitive biases when designing, thinking, analyzing, and making decisions based on data. Prerequisite(s): Data Science 603, 604 and admission to the Graduate Diploma in Data Science and Analytics; or Proficiency in Python and R programming, and successful completion of at least one mathematics course at either the undergraduate or graduate level and consent of the program. Antirequisite(s): Credit for Community Health Sciences 636 and Data Science 624 will not be allowed.