Master of Science, Innovation & Technology

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Total Degree Credits: 30

The Master of Innovation & Technology (MI&T) degree provides cutting edge opportunities to address present day challenges and develop technologies for the future. The college supports graduate research utilizing state-of-the-art experimental and/or computational research facilities under close faculty supervision in Logistics-Analytics and Big Data Analytics. Both thesis and project tracks are offered.

Upon completion of the Master of Science in Innovation & Technology Degree, students will be able to:

Apply knowledge of design IT principles in a defined industry problem.
Conduct research and apply knowledge based on these research skills.
Apply knowledge of managerial skills to coordinate and execute an industry project.
Demonstrate understanding of applied analysis of user requirements, research skills, managerial skills and IT based knowledge.
Analyze and properly use current computing techniques, methods and theories in an industry scenario.

Admissions Requirements

Admission decisions are based on consideration of the applicant’s previous academic records, statement of purpose, resume and letters of recommendations.

The following are the admissions requirements:

A bachelor degree in Engineering, Applied Sciences, or a closely related discipline from a regionally accredited university
A minimum GPA of 2.7 in the last 60-semester credits attempted
Graduate Record Exam (GRE) may be required for applicants with an undergraduate GPA of less than 3.25.
A letter of interest
Two letters of recommendations.

Master of Science in Innovation and Technology

Degree Core Requirements

ESI 5315 - Optimization and Simulation Credits: 3
MAP 5436 - Applied Math Credits: 3
QMB 5565 - Quantitative Empirical Research Methods Credits: 3
COP 5727 - Advanced Database Systems Design Credits: 3
CAP 5770 - Data Mining & Text Mining Credits: 3
CAP 5774 - Data Warehousing Credits: 3

Thesis or Project Option

Students select a two-part Thesis option for 6 credits or a one-part Project option for three credits. In either case, the total number of program credits to be earned is 30.

IDS 5950 - Project Credits: 3
IDS 5970 - Thesis 1 Credits: 3
IDS 5975 - Thesis 2 Credits: 3

Degree Program Tracks

Track: Logistics Analytics courses

MAN 5528 - Principles of Logistics/Transportation Systems Credits: 3
MAN 5596 - Global Supply Chain Management Credits: 3

Track: Big Data Analytics courses

CGS 5367 - Advanced Applied Information Credits: 3
CTS 5378 - Advanced Cloud Applications Credits: 3

Plan of Study for Logistics Analytics (30)

Plan of Study for Big Data Analytics (30)

Fall 1 (9)

MAP 5436 - Applied Math Credits: 3
QMB 5565 - Quantitative Empirical Research Methods Credits: 3
CGS 5367 - Advanced Applied Information Credits: 3

Spring 1 (9)

ESI 5315 - Optimization and Simulation Credits: 3
CAP 5774 - Data Warehousing Credits: 3
CTS 5378 - Advanced Cloud Applications Credits: 3

Fall 2 (9)

COP 5727 - Advanced Database Systems Design Credits: 3
CAP 5770 - Data Mining & Text Mining Credits: 3
Elective Credits: 3

IDS 5970 - Thesis 1 Credits: 3

Spring 2 (3)

IDS 5950 - Project Credits: 3
OR
IDS 5975 - Thesis 2 Credits: 3

Electives

CAP 5765 - Computational Data Analysis Credits: 3
CAP 5781 - Complex Modeling, Forecasting Techniques and Web Analytics Credits: 3
CIS 5616 - Advanced Business Intelligence Applications Credits: 3
ENT 5016 - Entrepreneurship and New Venture Creation Credits: 3
ENT 5930 - Innovation and Emerging Technologies Credits: 3

University Graduation Requirements

Satisfactory completion of 30 credits of approved graduate courses with a GPA of 3.0 or better.
Meeting any pre-requisites/deficiencies identified by the Graduate Student Advisor.
Compliance with all other university graduation requirements.