Keiser University’s Associate of Science degree in Artificial Intelligence prepares students with the foundation theories and practical applications of artificial intelligence, with a focus on simulating thinking, pattern recognition, decision-making, and automation using software-based systems. AI technologies such as machine learning, neural networks, and data-driven decision systems increasingly underpin modern applications, from chatbots and recommendation engines to autonomous systems like drones and smart devices. The program is designed to build skills in these core areas, supported by instruction in widely used programming languages (e.g., Python, Java) and platforms relevant to AI development.
Program Objectives
The following objectives are designed to meet Keiser University’s mission and goals:
Build a foundational understanding of artificial intelligence, including key concepts in machine learning, decision systems, and data processing.
Develop programming and computational thinking skills through hands-on experience with languages such as Python and Java.
Introduce core supporting technologies, including networking, cybersecurity, and web development, essential for modern AI applications.
Cultivate analytical, problem-solving, and ethical reasoning abilities in the context of AI development and deployment.
Prepare students for entry-level positions in AI-related fields or for a seamless transition into a bachelor’s degree in artificial intelligence or a related discipline.
Prerequisites for Major Courses
None.
Program Outline
To receive an Associate of Science degree in Artificial Intelligence, students must complete 60 credit hours as described below. The length of this program is approximately 20 months (this will vary if a student transfers in credits).
Lower Division Courses
Artificial Intelligence Major Courses (36.0 credit hours)
Python Programming
4.0 credit hours
Essentials of Networking
3.0 credit hours
Data Structures & Algorithms
4.0 credit hours
Java Programming I
4.0 credit hours
Discrete Mathematics and Probability
4.0 credit hours
Principles of Information Security
3.0 credit hours
Concepts of AI Programming
4.0 credit hours
Intro to Machine Learning
4.0 credit hours
Artificial Intelligence I
3.0 credit hours
COP1035C Python Programming 4.0 credit hours
3.0 credit hours
General Education Courses (24.0 credit hours)
Credit hours in parentheses indicate the required number of credits in each discipline.
Behavioral/Social Science (3.0 credit hours)
Introduction to Psychology
3.0 credit hours
Political Science
3.0 credit hours
Sociology
3.0 credit hours
Communications (3.0 credit hours)
Speech
3.0 credit hours
Computers (3.0 credit hours)
Introduction to Computers
3.0 credit hours
English (3.0 credit hours)
ENC1101 English Composition I
3.0 credit hours
ENC1102 English Composition II
3.0 credit hours
Humanities/Fine Arts (3.0 credit hours)
American Literature
3.0 credit hours
English Literature
3.0 credit hours
Mathematics (3.0 credit hours)
Intermediate Algebra
3.0 credit hours
College Algebra
3.0 credit hours
Natural Science (6.0 credit hours)
General Biology
3.0 credit hours
Advanced Biology
3.0 credit hours
General Chemistry
3.0 credit hours
Advanced Chemistry
3.0 credit hours
General Physics I
3.0 credit hours
General Physics II
3.0 credit hours
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