Courses

This short practical course is designed to provide a brief introduction to Linux operating system.

This short course is designed to provide a brief introduction to Python programming language to students with no prior knowledge of Python.

This one-day workshop is an introduction to the essential concepts and techniques for the statistical computing language R.

This course introduces the essential general programming concepts and techniques to a data analytics audience without prior programming experience.

This course in Deep Learning and Image Recognition will provide a practical, hands-on set of lectures on Deep Learning and Image Processing tools and techniques.

The course presents models and applications of sequential decision making under uncertainty.

This four-session course will focus on two of the more critical Big Data ethical issues at hand: bias and privacy. Its goal is to equip students with the ability to identify, understand, and discuss these the ethics of bias and privacy in the context of their work.

This course in python starts with introduction to the python programming language basic syntax and environment. It methodically builds up the learner's experience from the level of simple python statements and expressions to writing succinct, efficient and fast Python expressions and package the code in methods and classes.

Analytics Practicum is part of the co-operative educational agreement between MScA program and employers that provides off-campus work authorization for international students to pursue internships.

This course familiarizes students with the fundamentals of emergency management and homeland security.

This course will cover basic summary and inferential statistics and data visualization.

This course will focus on converting the tools of policy analysis into action and social change, addressing the regulatory, legal, and ethical issues affecting hazard and response management, privacy, and quarantine.

The course examines how different techniques are being applied to inform preparedness and planning decisions, in infrastructure, terrorism, supply chains, public health and other areas.

This course focuses on evidence-based communication strategies, tools and tactics in crisis situations.

Students will learn how to be good members and effective leaders of teams, committees, and other decision-making and problem-solving groups and develop strategies to build partnerships and establish networks to ensure effective response when a disaster strikes.

This course is designed to provide information crucial to monitoring the health of the public and responding to outbreaks.

This course provides the conceptual and technical knowledge necessary to conceptualize complex dynamic policy problems, formulate appropriate simulation models, and use models for policy analysis.

This course examines the various sectors that make up critical infrastructure, their associated dependencies and interdependencies, and the strategies employed at the local, state and federals levels of government and the private sector to assess vulnerability, minimize risk and confront natural and intentional threats to these vital sectors.

This course will teach students better manage and prepare for emergencies through effective information management.

This course is designed to cover the basic principles of radiation biology as it pertains to radiation interactions with biological systems, the short and long term consequences, regulatory issues and the underlying science, nuclear and radiological accidents and health effects, radiological terrorism, and countermeasures.