What is a Masters of Science in Information Technology Degree?

The Master of Science in Information Technology is a one to three years Master Degree, depending on the program, some may even start with 2 year preparation classes. It covers various areas of information technology and may be focused on software engineering, software development, computer programming, software testing, or computer security.

A master’s degree in information technology could prepare you with the communication skills, critical thinking abilities, and technical competencies to help advance your career. You will have the opportunity to apply appropriate technologies in the analysis and design of information systems, as well as assess ethical, legal, and social issues.

The Master of Science in Information Technology program is designed to provide you with an integrated design and technology background that may help you advance your career. You will have the opportunity to study:
-The theory, principles, and practices of information systems
-How to employ project management skills
-How to analyze data to solve complex problems

Business Intelligence: Focus on the business side of technology and study analysis and development of decision support systems, business intelligence, knowledge acquisition and representation models, data mining concepts, algorithms, and applications.

Entrepreneurship: Study the theories and practices related to the startup, development, and management of a new business, product, or service. Examine the functions of management as they apply to the small business environment and the theory and practices of corporate venturing. Study strategies for creating a workable business plan. Participate in a virtual practicum and apply strategies and practices to a startup business. Review methods for identifying and pursuing venture opportunities. Experience the entrepreneurial group process through strategic development in a team environment.

Information Security and Assurance: In today’s world, protection of data is serious business. Explore everything from fundamentals such as viruses, worms, and other malicious software to more high-level aspects of IT security like network defense, ethical hacking, and computer forensics.

Project Management: Focus on strategic project management with an emphasis on planning, executing, and controlling phases of a project life cycle. Utilize current software to achieve project goals and objectives. Explore the principles, tools, and techniques for controlling project cost and scheduling. Analyze project risk, quality, and legal and ethical considerations in contracting and procurement. Study to develop skills to help increase the bottom line for organizations in a variety of industries.

SPECIALIZATION COURSES (24 Credits)
*Students entering the program who do not possess a bachelor’s degree in information technology or a comparable field of study must take IT 501: Principles of Information Technology their first term in place of an IT elective.

IT 521: DECISION SUPPORT SYSTEMS (4 Credits)
This course provides a detailed overview of decision-making systems, models, and support in business. The course covers many fundamental topics including: analysis and development of decision support systems, business intelligence, knowledge acquisition and representation, knowledge management, intelligent systems over the Internet, and advanced intelligent systems.

IT 522: KNOWLEDGE-BASED MANAGEMENT SYSTEMS (4 Credits)
This course provides a detailed overview of knowledge-based systems techniques and applications. Topics include symbolic structures and semantics, knowledge representation models, search techniques related to problem solving, knowledge engineering, knowledge and domain classification models, configuration models, and diagnosis and troubleshooting methodologies.

IT 523: DATA WAREHOUSING AND DATA MINING (4 Credits)
This course discusses data warehousing and data mining concepts and algorithms. Topics covered in this course include: data mining functionalities, data preparation and preprocessing, data warehousing architectures and implementations, data cube computations, data generalization and conceptualization, pattern recognition, association rules and correlation analysis, classification and prediction techniques, analysis of data clusters, and data mining application to business, text, spatial, and Web data.