Artificial Intelligence / Master of Science
Program: MS-ARIN-1
A Master of Science in Artificial Intelligence degree equips students with in-depth knowledge and practical skills needed to build and implement modern AI systems. The degree provides the necessary theoretical background in machine learning and artificial intelligence, knowledge related to the application of artificial intelligence in computing systems and the ethical implication in the development and use of artificial intelligence. A graduate of the MSAI program will be prepared for a wide range of careers where artificial intelligence is applied, including work in industry or the government, or further graduate studies.
Degree Offered: Master of Science
Total Credit Hours: 34
To complete the M.S. in AI, students will need to complete a minimum of 34 credit hours, which include 25 credit hours in core courses, including a three credit hour Master’s Project; six credit hours of foundation courses; and three credit hours of elective courses. Elective courses may be substituted for foundation courses for students with sufficient background (i.e. baccalaureate degree in computer science or a closely related field).
| Code | Title | Hours |
|---|---|---|
| Foundation Courses | ||
| CPSC 50100 | Programming Fundamentals | 3 |
| DATA 50000 | Mathematics for Data Scientists | 3 |
| Core Courses | ||
| CPSC 57100 | Artificial Intelligence 1 | 3 |
| CPSC 57500 | Ethics in Artificial Intelligence | 1 |
| CPSC 57700 | Machine Learning Operations | 3 |
| CPSC 57900 | Generative Artificial Intelligence | 3 |
| DATA 51100 | Statistical Programming | 3 |
| DATA 54000 | Large-Scale Data Storage Systems | 3 |
| DATA 55100 | Unsupervised Machine Learning | 3 |
| DATA 56000 | Neural Networks and Deep Learning | 3 |
| CPSC 69300 | Artificial Intelligence Master’s Project | 3 |
| Electives | ||
| Select one of the following: | 3 | |
| Artificial Intelligence 2 | ||
| Natural Language Processing | ||
| Applied AI for Business Apps | ||
| Reinforcement Learning | ||
| Data Mining and Analytics | ||
| Multivariate Data Analysis | ||
| Supervised Machine Learning | ||
| Digital Image Processing | ||
| Data Mining for Cyber Security | ||
| Total Hours | 34 | |
Full Admission
To be accepted for admission into the program, a student must present the following credentials.
- A baccalaureate degree from a regionally accredited institution of higher education.
- A minimum undergraduate GPA of 3.0 on a 4.0 scale.
- An application for graduation admission, accompanied by an application fee.
- Official transcripts from all institutions of higher education attended.
- Two letters of recommendation.
Please note: International students are required to have a TOEFL test score greater than 79 or an IELTS test score greater than 6.5.
Provisional Admission
Under certain circumstances, students who do not meet one or more of the requirements for full admission may be admitted to the program on a provisional basis. Provisional admission is most commonly offered to applicants who earned an undergraduate GPA less than 3.0. Students admitted with provisional status will be considered for full admission only after they have attempted nine credit hours in the program and earned a GPA of 3.0 out of 4.0. Provisionally-admitted students who have not attained a minimum GPA of 3.0 out of 4.0 after attempting nine credit hours of MSAI coursework will be dismissed from the MSAI program.
Student-at-Large
A student-at-large is not a degree candidate. To be admitted as a student-at-large, the applicant must submit official documentation of a baccalaureate degree from a regionally accredited institution of higher education and complete a modified application form. The decision to admit an at-large student to graduate courses belongs to the Graduate Program Director, whose decision is based on an evaluation of the applicant’s undergraduate coursework and possibly an interview. However, should the student decide to apply for full admission status at a later time, but within five years of course completion, only a maximum of nine semester hours of graduate coursework completed as a student-at-large can be applied toward an advanced degree, and only courses with grades of B or better will count toward the degree.
Transfer of Graduate Credit
A student entering the MSAI program with appropriate prior graduate coursework in computer science, data science or artificial intelligence may have a maximum of nine credit hours applied to the MSAI degree. Course credits eligible for transfer consideration must meet the following criteria:
- All transfer credit must have been earned prior to matriculation in the MSAI program.
- The coursework must have been completed at a regionally accredited graduate school.
- A minimum grade of B must have been earned for the course.
- The coursework must have an equivalent in the MSAI curriculum.
- Courses from outside the United States will be considered if they are evaluated as graduate level by the Office of Admission or the Commission on Accreditation of the American Council on Education.
- Credit for prior learning is not awarded for graduate courses.
International Students
International students are required to meet all the admission requirements for full or provisional admission and also the admission requirements specified in the General Information section of this Catalog entitled Entering International Students.
Time Limitation for Completing the Program
A student must complete all graduation requirements within seven years from completion of the first graduate course taken at Lewis University. Students remain under the requirement of the catalog in effect at the time of matriculation unless they discontinue attendance for two consecutive years or more, in which case they will follow the catalog in effect upon their return.
Graduation Requirements
To complete the MSAI degree, a student must earn a minimum of 34 credit hours, 25 hours of core curriculum, and nine credit hours of foundation classes and electives. Foundation coursework may be waived for students with sufficient background in programming and mathematics.
Comprehensive Examination
There is no comprehensive examination in this program.
Culminating Experience
The student must complete a three credit-hour of Master’s Project to earn the MSAI degree. This experience is fulfilled by completing CPSC 69300 Artificial Intelligence Master’s Project. In this course, the student must develop a solution to an AI related problem, write a capstone paper, and give a capstone presentation, unless some other method of dissemination is approved by the capstone adviser and the Graduate Program Director.