Health Data Science (HDS)

Fundamentals of data wrangling and programming using R will be taught in this class. Students will experience the science and art of data wrangling with various datasets. This is a technical course and students will be required to program in R.

Key programming techniques in data analysis such as exploratory data analysis and statistical modeling. The course requires ability to analyze data and program independently in R.

Applies computational and statistical techniques to address or gain insight into a real-world problem. Provides a comprehensive overview of data science and AI, the practice of obtaining, modeling, and interpreting data. Explores the process of how to structure applications of analytic methods for analyzing administrative, environmental, social, public health, and clinical systems data. Introduces the data analytic process, which includes analytic planning, exploratory data analysis, multivariate statistical methods, statistical inference, and practical interpretation of results.

R-based course that builds upon supervised learning algorithms and moves forward into unsupervised learning topics. Proficient R programming skills will be required to construct predictive models.

Explores the art of data visualization, communications, organizational psychology and change management with the goal of driving operational, tactical and strategic decision-making within healthcare organizations. Focuses on how to use data to a) provide knowledge in the most effective manner possible (i.e., provide relevant, timely and complete data to each audience member in a clear and understandable manner that conveys important meaning, is actionable and can affect understanding, behavior and decisions) and b) provide knowledge in the most efficient manner possible (i.e., minimize noise, complexity and unnecessary data or detail given each audience's needs and roles).

Presents a multidisciplinary framework and methodology to promote the integration of scientific evidence into healthcare practice, policy and research. Addresses Implementation Science and the evaluation of evidence, stakeholder/organizational readiness, systems thinking, and approaches to implementation. Provides opportunities to develop design strategies, assess data needs, and complete a project implementation plan.

Critically analyzes and develops proposals for HDS Capstone Projects. All parts of a proposal are drafted, critiqued, and revised in accordance with the Capstone Guidelines of the HDS program.

Presentation of a portfolio of experiences in the degree program to demonstrate proficiencies in HDS core competencies.