Artificial Intelligence Admission Criteria
Approved University Admission
1-page essay stating the reasons for applying to the program and career goals
Resume reflecting work experience and educational background
Official GRE or GMAT Data (Note: Student must have a Graduate Admissions Index of 980)
*Formal Admission to the MS-CIS program
Students should submit official transcripts and GRE scores to the Office of Admissions. Program specific requirements such as essays, letter of recommendation, resumes, and/or writing samples should be submitted directly to Graduate Admissions.
Artificial Intelligence Concentrations
Prerequisite Leveling – 18 semester hours
3 s.h. of programming or data structures using an object-oriented programming language
3 s.h. of programming or data structures using and object-oriented programming language
3 s.h. of information systems in organizations
3 s.h. of Calculus, Discrete Structures, Discrete Mathematics, Operations Research, or Management Science
3 s.h. of Statistics
3 s.h. of Management
(Documentation of prior learning which satisfies program prerequisite knowledge in part of full is required for determination of equivalencies and/or waivers. The student may directly submit to the CIS Graduate Program Advisor a portfolio of work for evaluation for exempting one or more prerequisite/leveling course. Such work may include non-credit or non-academic course work, certifications held and other experiential knowledge in subject area. Such exemption will be solely at the discretion of the CIS Graduate Program Advisor, and may involve interviews, tests, or contact of references. No such waiver for non-academic experience will be done for any part of the 36 s.h. beyond the pre-req/leveling courses).
Core – 15 semester hours
COSC 6336 Database Design
COSC 6342 Software Engineering/Project Management
COSC 6350 System Analysis and Design
COSC 6339 Network Design and Management
COSC 6325 Policy, Strategy, and Ethical Issues in IS
Specialization – 18 semester hours
Artificial Intelligence Concentration
Must choose 9 semester hours (3 courses) from the following to fulfill the artificial intelligence concentration requirements:
COSC 6370 Advanced Topics in Artificial Intelligence
COSC 6349 Computer Vision and Image Processing
COSC 6348 Natural Language Processing
COSC 6328 Deep Learning
Select 9 semester hours (3 courses) from the list below or any other graduate level COSC or GMNG course. 2 Thesis courses are required if Thesis Option is approved by Thesis Advisor. (See restrictions at Thesis Options for additional information.)
COSC 6300 Special Topics in CS/IS
COSC 6310 Multimedia Development and Programming
COSC 6329 Data Warehousing and Data Mining
COSC 6337 Web Mining and Info Retrieval
COSC 6328 Deep Learning
COSC 6341 Internet Programming
COSC 6343 Intelligent Agents and Apps
COSC 6347 System Admin
COSC 6348 Natural Language Processing
COSC 6349 Computer Vision and Image Processing
COSC 6351 Decision Support Systems
COSC 6353 Info Systems Security
COSC 6357 Web Engineering
COSC 6359 Cloud Computing
COSC 6344 Advanced IT Project Management
COSC 6315 Data Science using Machine Learning
COSC 6370 Advanced Topics in Artificial Intelligence
COSC 6349 Computer Vision and Image Processing
COSC 6348 Natural Language Processing
COSC 6328 Deep Learning
Integration Course – 3 semester hours
COSC 6390 Integrating the Enterprise, IS Function/Technologies
Thesis Option:
COSC 6308 Master’s Thesis
COSC 6309 Master’s Thesis
Academically strong students may advance their knowledge in a particular area of CIS via this option. Pre-approval by faculty under which student has obtained a 3.0 GPA (Thesis Advisor) is required.
Internship Option:
Students who prefer obtaining more industry experience before graduation could choose the internship track. This track allows students to start taking internship from first semester. Students choose this track must complete 6 semester hours of internship courses. They could be a combination of COSC 6105, COSC 6205, and COSC 6305. Program director approval is needed for Internship track.