Students will learn a theoretical & applied process to identify risks in every job description in their respective public safety agency. From this basis of risk identification, students will gain skills & knowledge to design & update control measures to proactively prevent tragedies from occurring. Final project will be a development of an instrument to recognize, prioritize, mobilize to address identified public safety risks in community/agency.

Explores the Constitution as the ethical compass that guides the work of public safety professionals and cement a fundamental understanding of the U.S. Constitution and the subsequent 27 amendments. Students will develop a detailed understanding of both the powers and limitations that arise from the Bill of Rights, and closely examine the evolution of the rule of law that frames and guides their work.

This course is designed for capstone project teams to meet in groups, with advisors, and with clients to advance work on their projects.

This course is designed for capstone project teams to meet in groups, with advisors, and with clients to advance work on their projects.

Through a step-by-step process students learn to conduct statistical analyses to examine, evaluate, and share relevant public safety related data. Students also learn how to make practical interpretations of the data and methods for decision-making.

Designed for capstone project teams to meet in groups with advisors and clients to advance work on their projects. Capstone course for MSDS Online students.

Comprehensive introduction to predictive modeling, a cornerstone of data science and machine learning. Learn the fundamental concepts, techniques, and tools used to build models while emphasizing both theoretical understanding and practical applications. The topics include we will cover are an in-depth analysis of linear models and different variants, their extension to generalized linear models, and an introduction to nonparametric regression.

Examines joint operations and incident command for complex events. Emphasis will be placed on command structure, continuity of operations, public safety response to community/public health emergencies, occupational health and safety, local systems and resources, inter-agency cooperation, and communications and technology support. Students will engage public safety response issues and apply their knowledge through scenario exercises.

This course covers fundamentals of data mining and machine learning within a common statistical framework. Topics include regression, classification, clustering, resampling, regularization, tree-based methods, ensembles, boosting, and Support Vector Machines. Coursework is conducted in the R programming language.

Focuses on the application of communication skills and principles in the context of public safety. Students will gain understanding and practice in engaging communities around such challenging issues as inequality and power; interactions in the aftermath of tragedy; officer fear and anger; historical, political, and economic divides; implicit biases and stereotype threat; and the importance of building coalitions across boundaries.