Graduate Course Descriptions

This course validates BSN equivalent competencies in nursing leadership, research and community health as outlined in the Essentials of Baccalaureate Education for Professional Nursing Practice (2008). In this course the RN students (who do not have a BSN degree) present a completed professional portfolio to demonstrate knowledge foundational for MSN study. (Prerequisite: RN with a non-nursing baccalaureate degree).

Advanced nursing roles will be analyzed in terms of their major components: consultant, change agent, clinician, educator, mentor, researcher, leader and manager within the context of changing educational institutions and health care delivery system. The process of socialization into the advanced nursing role is explored, and strategies for effective role implementation and evaluation are discussed. Practical strategies for role transition and development will be reviewed.

Examines the development of the nurse practitioner role and competencies, engaging the student in the use of select theories around family dynamics, relationships, quality & safety, and leadership to successfully operationalize the role of the FNP. Students learn about information systems and technology and the application of those systems to improve quality, safety, outcomes, and efficiency in health care.

Examines the development of the nurse informaticist and competencies. This course focuses on the foundational knowledge for understanding and practicing nursing informatics in healthcare settings. Students are engaged in the use of selected theories and models that support the role of nursing informatics and the application of nursing information technology in promoting management and quality of healthcare.

Focuses on the social, political, and economic factors that influence health policy decisions. Students will examine the legal, ethical, financial, and political foundations of the health care delivery system and its function as a social institution. The role of the nurse in advanced practice in influencing policy decisions and in addressing the needs of vulnerable and culturally diverse populations will be emphasized.

This course is designed to provide the students with an exposure to the most commonly used statistical concepts, methods, techniques, and their applications to business problems. We cover the basic concepts of business statistics and data analysis integrated in a contemporary spreadsheet environment. The course emphasizes practical applications and business decision-making.

This course introduces the principles, concepts, techniques, and tools for visualizing information in large complex data sets. Unlike scientific visualization, which focuses on the presentation of data that has a spatial or physical correspondence, data visualization focuses on mapping complex, abstract information to a physical representation. The development of effective visualization strategies is crucial for not only facilitating an understanding of large complex data sets but also for driving knowledge discovery and the decision-making processes in a given domain. In this course, students will learn the key principles involved in data visualization and will explore a wide range of visualization approaches that can be applied for understanding complex data across different data types. Specifically, techniques for visualizing: one-dimensional data (e.g., temporal data), two-dimensional data (e.g., geospatial data), multidimensional data (e.g., mapping relational data in n-dimens

This course develops students’ process modeling, data analytics, and decision-making skills regarding the management of people in an organization. Analytics includes data collection, organization, storage, analysis, and all the tools and techniques used to describe current processes, assess and address challenges, and plan for changes. Before managers can make use of people analytics, they must understand and describe human resource processes as well as relevant databases, information systems, and other information and resources available. Students in this people analytics course will develop an understanding of traditional work processes, HR management requirements, and HR information system architectures in the context of data-driven approaches to decision-making about people in organizations. Students will learn to model HR processes, develop queries, analyze data, and generate reports to make strategic decisions in areas of HR practice such as selection, compensation, performan

Provide students with a foundational understanding of applying marketing data analytics to business decisions and strategy. The course will review the process and components of data analysis, including planning the analysis, basic properties of statistics, and reporting results. Students will learn how to map data to marketing challenges, apply basic statistics to marketing analyses, communicate data results in meaningful ways, and support organizations in effectively leveraging marketing data. Special emphasis is given to translating data into meaningful and actionable business insights. This course does not assume any prior knowledge in statistics.

Provides the advanced knowledge and skills for holistic health assessment within the context of advanced nursing practice. This course emphasizes the collection, interpretation, and synthesis of relevant historical, genetic, biological, cultural, psychosocial, and physical data for the development of a comprehensive and holistic health assessment. Evidence-based practice concepts related to health promotion/disease prevention are addressed.