In this course students will develop a data science tool kit they may use to investigate research questions. The methodological approaches students will be exposed to include linear regression, classification, resampling methods, linear model selection, tree-based methods, unsupervised learning, and network analysis. Ethical approaches to the use of data science are reviewed in this class.

This course provides the foundations for master's level nursing practice to advance nursing practice. The student is required to integrate theory, evidence, clinical judgment and research to improve population health outcomes. Evidence-based practice is applied to the role of the master's level nurse and will examine the ethical implications of research and translational scholarship. The student must be able to articulate how evidence is the basis for practice decisions and include the credibility and relevance of the sources. Practice guidelines will be discussed and their impact on health outcomes.

This integrative clinical capstone is the final course in the Master of Science in Nursing Health Care Leadership program. All other required coursework must have been completed prior to receiving approval to register for this course. Students in this course will have the opportunity to apply the principles learned in the entire program of study and will demonstrate competence by integrating and applying those skills to a real-world scenario. The course culminates in a project focused on enhancing nursing practice by improving population health outcomes. Student will be required to verbally present and defend their project and achieved outcomes.

The course further develops and refines critical thinking skills be student participation in increasingly complex simulated clinical scenarios and de-briefings. Students prepare for the care of patients in a simulated environment, using the nursing process, to demonstrate the effective delivery of planned patient care.