Artificial Intelligence, MS
The vision of the MS in artificial intelligence graduate program is to cultivate an innovative research and teaching ecosystem that advances computational and AI-driven solutions, empowering society to address complex challenges in an era of rapid technological transformation.
Program Related Information
Program Contact
Michelle Perone, Graduate Advisor
402.554.3819
mperone@unomaha.edu
Program Website
Fast Track
The Department of Computer Science has developed a Fast Track program for highly qualified and motivated students providing the opportunity to complete a bachelor’s degree and a master’s degree in an accelerated time frame. With Fast Track, students may count up to nine graduate credit hours towards the completion of their undergraduate program as well as the graduate degree program. Students will work with both undergraduate and graduate advisors to ensure graduate classes selected will count toward both programs, should a student wish to earn a graduate degree in a separate College of Information Science & Technology (CIST) area than their undergraduate degree.
Program Specifics:
- This program is available for undergraduate students pursuing any CIST undergraduate degree desiring to pursue an MS in either the same or a related CIST field.
- Students must have completed no less than 60 undergraduate hours.
- Students must have a minimum undergraduate GPA of 3.0.
- Students must complete the Fast Track Approval form and obtain all signatures and submit to the Office of Graduate Studies prior to first enrollment in a graduate course.
- Students will work with their undergraduate advisor to register for the graduate courses.
- A minimum cumulative GPA of 3.0 is required for graduate coursework to remain in good standing.
- Students remain undergraduates until they meet all the requirements for the undergraduate degree and are eligible for all rights and privileges granted undergraduate status including financial aid.
- Near the end of the undergraduate program, formal application to the graduate program is required. All applicants will need to meet any other admission requirements established for the MS in selected CIST program. The application fee will be waived if the applicant contacts the Office of Graduate Studies for a fee waiver code prior to submitting the MS application.
- Admission to Fast Track does NOT guarantee admission to the graduate program.
- The admit term must be after the completion term of the undergraduate degree.
Admissions
General Application Requirements and Admission Criteria
Program-Specific Requirements
Application Deadlines
Applicants are strongly encouraged to apply as early as possible, especially if applying for assistantships or scholarships. Some scholarships may have earlier deadlines or run out of funding.
- Spring 2027:
- October 1 for international applicants who are required to secure a new student visa
- November 1 for all other applicants
- Summer 2027:
- March 1 for international applicants who are required to secure a new student visa
- March 15 for all other applicants
- Fall 2027:
- May 1 for international applicants who are required to secure a new student visa
- July 1 for all other applicants
Other Requirements
- The minimum undergraduate grade point average (GPA) requirement for the MS in artificial intelligence program is 3.0 or equivalent score on a 4.0 scale. Applicants should have the equivalent of a four-year undergraduate degree.
- Entrance Exam: The Graduate Record Exam (GRE) is not required.
- English Language Proficiency: Applicants are required to have a command of oral and written English. Those who do not hold a baccalaureate or other advanced degree from the United States, OR a baccalaureate or other advanced degree from a predetermined country on the waiver list, must meet the minimum language proficiency score requirement in order to be considered for admission.
- Internet-based TOEFL: 80, IELTS: 6.5, PTE: 53, Duolingo: 110
- Resume: Submit a detailed resume indicating your work experience and background.
- OPTIONAL: One letter of recommendation from a reference who can evaluate your work and/or academic achievements.
- OPTIONAL: Application for Graduate Assistant Position
- If interested in applying for Graduate Assistant (GA) positions, please submit a letter stating your research area interests and why you feel you would make a good GA. Please note that GA positions will be considered after admission and program admission is not a guarantee of receiving a GA position.
Degree Requirements
A total of 30 credit hours is required for a MS AI degree. At least 15 credit hours must consist of graduate only 8xx0 coursework. Coursework must meet the distribution requirements shown below:
| Code | Title | Credits |
|---|---|---|
| Core Courses | ||
| CSCI 8456 | PRINCIPLES OF ARTIFICIAL INTELLIGENCE 1 | 3 |
| CSCI 8110 | ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE | 3 |
| CSCI 8450 | ADVANCED TOPICS IN NATURAL LANGUAGE UNDERSTANDING | 3 |
| Required Concentration - Select a Concentration | 12 | |
| Exit Option - Select One Path | 6 | |
| Thesis Option - Complete 6 hours of thesis credit distributed over at least two terms | ||
| THESIS | ||
| Project Option - Complete 6 hours of project credit distributed over at least two terms | ||
| THESIS EQUIVALENT PROJECT IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | ||
| Capstone Option - Complete 3 hours of capstone and 3 hours of additional electives | ||
| MASTER OF SCIENCE CAPSTONE | ||
| Additional elective coursework | 3-6 | |
AIML 8xxx | Any AIML graduate courses may be used as electives if not applied elsewhere in the plan of study (excluding project and thesis) | |
CSCI 8xxx | Any CSCI graduate courses may be used as electives if not applied elsewhere in the plan of study. | |
| LINEAR ALGEBRA FOR ADVANCED COMPUTING AND AI | ||
| SPECIAL TOPICS IN CYBERSECURITY | ||
| NETWORK SECURITY | ||
| BUSINESS INTELLIGENCE | ||
| DECISION SUPPORT SYSTEMS | ||
| FOUNDATIONS OF INFORMATION SYSTEMS 2 | ||
| Total Hours Required | 30 | |
- 1
Students who have taken CSCI 4450 or CSCI 8456 with a grade of “B-" or better before entering the MSAI program can replace this course with an elective course of 3 credit hours.
- 2
ISQA 8030 may be used to meet elective credit requirements in the MS AI program with permission of both the AI and MIS graduate program committees.
Concentrations
Data Analytics Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8590 | FUNDAMENTALS OF DEEP LEARNING | 3 |
| Complete 9 additional hours from the following. | 9 | |
| BUSINESS FORECASTING | ||
| BUSINESS INTELLIGENCE AND REPORTING | ||
| DATA ANALYSIS FROM SCRATCH | ||
| DESIGN AND ANALYSIS OF ALGORITHMS | ||
| DATA WAREHOUSING AND DATA MINING | ||
| INDEPENDENT STUDY | ||
| ADVANCED STATISTICAL METHODS FOR IS&T | ||
| DATA MINING: THEORY AND PRACTICE | ||
| INTRODUCTION TO DATA SCIENCE | ||
| EXPLORATORY DATA VISUALIZATION AND QUANTIFICATION | ||
| Total Credits | 12 | |
Computer Vision Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8300 | IMAGE PROCESSING AND COMPUTER VISION | 3 |
| Complete 9 additional hours from the following. | 9 | |
| ALGORITHMIC GRAPH THEORY | ||
| DESIGN AND ANALYSIS OF ALGORITHMS | ||
| PATTERN RECOGNITION | ||
| FUNDAMENTALS OF DEEP LEARNING | ||
| INDEPENDENT STUDY | ||
| APPLIED STATISTICAL MACHINE LEARNING | ||
| Total Credits | 12 | |
Fundamentals of AI Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8080 | DESIGN AND ANALYSIS OF ALGORITHMS | 3 |
| Complete 9 additional hours from the following. | 9 | |
| ALGORITHMIC GRAPH THEORY | ||
| FUNDAMENTALS OF DEEP LEARNING | ||
| AUTOMATA, COMPUTABILITY, AND FORMAL LANGUAGES | ||
| INDEPENDENT STUDY | ||
| ADVANCED STATISTICAL METHODS FOR IS&T | ||
| DATA MINING: THEORY AND PRACTICE | ||
| Total Credits | 12 | |
Machine Learning Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8590 | FUNDAMENTALS OF DEEP LEARNING | 3 |
| Complete 9 additional hours from the following. | 9 | |
| DESIGN AND ANALYSIS OF ALGORITHMS | ||
| MACHINE LEARNING FOR TEXT | ||
| PATTERN RECOGNITION | ||
| INDEPENDENT STUDY | ||
| INTRODUCTION TO MACHINE LEARNING AND DATA MINING | ||
| Total Credits | 12 | |
Natural Language Understanding Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8360 | MACHINE LEARNING FOR TEXT | 3 |
| Complete 9 hours from the following. | ||
| DESIGN AND ANALYSIS OF ALGORITHMS | ||
| FUNDAMENTALS OF DEEP LEARNING | ||
| AUTOMATA, COMPUTABILITY, AND FORMAL LANGUAGES | ||
| GRADUATE INTERNSHIP IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | ||
| INDEPENDENT STUDY | ||
| INTRODUCTION TO MACHINE LEARNING AND DATA MINING | ||
| PATTERN RECOGNITION | ||
| Total Credits | 3 | |
Robotics Concentration
| Code | Title | Credits |
|---|---|---|
| Required Course | ||
| CSCI 8460 | FUNDAMENTALS OF ROBOTICS | 3 |
| Complete 9 hours from the following. | 9 | |
| ALGORITHMIC GRAPH THEORY | ||
| DESIGN AND ANALYSIS OF ALGORITHMS | ||
| IMAGE PROCESSING AND COMPUTER VISION | ||
| MULTI-AGENT SYSTEMS AND GAME THEORY | ||
| ALGORITHMS FOR ROBOTICS | ||
| INDEPENDENT STUDY | ||
| EXPLORATORY DATA VISUALIZATION AND QUANTIFICATION | ||
| Total Credits | 12 | |