30000

DST 30000 LEAN SIX SIGMA (3)

Understanding of Lean Six Sigma concepts and its methodologies with the goal of improved project management skills, problem solving, and more effective cross functionality.  Defining a problem and implementing solutions that are linked to the underlying root causes and delivering  improvements that are efficient, cost effective, consistent, reliable, and sustainable.   Prerequisite: MAT 20044 Introduction to Statistics or OAD 30763 Business Statistics.

DST 30003 DATA MINING (3)

This course introduces the major quantitative models designed for competitive, and system forecasting in today's complex and increasingly large data-gathering business environment. The course is useful for multiple disciplines, including marketing, finance, and health care. Topics include statistical quality control, exponential smoothing, and seasonally adjusted trend analysis. Emphasis is placed on a general understanding of theory, mechanics, application potential, available software packages, and templates.  Prerequisite: MAT 20044 Introduction to Statistics or OAD 30763 Business Statistics.

DST 30006 CYBER SECURITY (4)

This course explores advanced topics in cyber security. Students will be exposed to a wide spectrum of security activities, methods, methodologies, and procedures with emphasis on practical aspects of Information Security.  Topics include security principles, threats, attacks, security models, security policies, an overview of authentication, encryption, and certifications, security detection, business risk analysis, protection of information assets, examination of pre- and post-incident procedures, and an overview of the information security evaluation.  Prerequisite: DST 20003 Network Security.

DST 30009 DATA VISUALIZATION (3)

An exposure to visual representation methods and techniques that facilitate the understanding of complex data.  Students will be able to present a visual interpretation of data, and improve comprehension, communication, and decision making.  The course covers how the human visual system processes and perceives images, good design practices for visualization, how to use existing tools to make visualizations, collecting data from web sites with Python, and programming interactive web-based visualizations.  Prerequisites: ITS 16163 Introduction to Computer Programming