Program Description
The Master of Science in Artificial Intelligence (MSAI) program is for students who desire to acquire advanced knowledge in the rapidly growing field of Artificial Intelligence (AI). Its comprehensive curriculum covers the core foundations of artificial intelligence, encompassing computer science, data science, mathematics, statistics, as well as contemporary AI models and frameworks. Students will acquire the skills necessary for developing practical applications in both industry and academic contexts. With continuously emerging AI technologies, this program is designed to provide the foundation needed to be successful and agile enough to bring new and emergent technologies to students.
Goals and Objectives
The Master of Science in Artificial Intelligence (MSAI) degree is designed to prepare professionals who will have the skills to:
- Analyze and implement fundamental algorithms that drive current Artificial Intelligence systems.
- Describe and understand the under laying statical, data science, and mathematical methods required for modern AI algorithms and models.
- Apply AI techniques to solve real-world problems across business, industry, and government sectors.
- Make informal and ethical decisions in the development of Artificial Intelligence solutions.
Program Completion
The program can be completed on a full- or part-time basis, with classes offered in three academic terms, fall, spring and summer. Time to complete depends upon the number of credit hours taken per semester and the number of knowledge support courses needed. Full-time students (6 credit hours per semester) can complete the program in four semesters. Students must complete the program within 5 years of the semester of their admission.
Admission Requirements Specific to the MSAI
The Dakota State University Masters of Science in Artificial Intelligence program seeks highly motivated individuals with education and professional credentials that will enable them to be successful graduate students. Admission to the program is based upon a combination of the following requirements:
- A baccalaureate degree in artificial intelligence, computer science, information systems, or closely related field from an institution of higher education with full regional accreditation for that degree. International students must have an undergraduate (bachelor’s) degree that is the equivalent to a four-year undergraduate degree in the U.S.
- Students who have not earned a baccalaureate degree in artificial intelligence, computer science or closely related field from an institution of higher education with full regional accreditation for that degree. International students must have an undergraduate (bachelor’s) degree that is the equivalent to a four-year undergraduate degree in the U.S.
- Minimum undergraduate grade point average of 3.0 on a 4.0 scale (or equivalent to an alternative grading system).
- Students who are accepted into the program but do not hold a B.S. in Artificial Intelligence or Computer Science may be required to show competency areas such as Computer Programming, Artificial Intelligence/Machine Learning, Mathematics, and Statistics. These competencies may be met with transcripted coursework or less-formal means such as experiences which demonstrate to the Admissions Committee gained competence in a knowledge area. Any remaining knowledge deficiency requirements will be included as part of the student’s formal Plan of Study (POS) as additional required credits.
Program Faculty
Mark Spanier (Program Chair), Austin O’Brien, Jason Mixon, John Hastings, Abid Mehmood, Jared Soundy, Khandaker Ahmed
Program Required Coursework
The program requires 30 credits beyond the baccalaureate. All students must take five core courses (15 credit hours), five elective courses (15 credit hours). Core courses build upon the knowledge support courses or appropriate experience.
Students who do not meet specific admission requirements may have to take foundational classes as part of their coursework that gets added to their program of study.
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