COURSE CURRICULUM

The Master of Science in Artificial Intelligence program at Auburn University at Montgomery offers a comprehensive curriculum designed to equip students with the technical expertise, analytical skills, and strategic understanding needed to excel in the rapidly evolving field of AI. The program begins with foundational courses in business statistics, programming, and management information systems, including Java, C++, Visual Basic, and object-oriented design, providing students with a strong computational and analytical foundation. Building on this base, students progress to specialized AI courses such as Machine Intelligence Environments, AI in Business Operations, AI Automation, Large Language Models, AI Strategy and Leadership, AI in Investment Management, and Machine Learning Theory and Applications, which prepare them to design, implement, and evaluate intelligent systems. Practical, hands-on courses in data visualization, data mining, deep learning, and applied business analytics allow students to interpret complex datasets and make informed decisions. The curriculum also emphasizes real-world application through capstone projects, independent study, and internships, giving students the opportunity to integrate theoretical knowledge with practical solutions in AI deployment, enterprise systems, and innovation management. Additionally, students study information systems, data storage technology, network security, and enterprise process integration, enabling them to understand AI within broader organizational and technological contexts. Courses in ethical issues, technology law, and professional leadership ensure that graduates are prepared to address the societal and managerial implications of AI. With a minimum of 30 credit hours, the program offers both thesis and non-thesis options to support academic research or industry-focused careers. Overall, the curriculum blends rigorous technical instruction with applied learning and strategic insight, equipping graduates with the knowledge, skills, and ethical perspective necessary to pursue careers in data science, AI development, machine learning applications, business analytics, and technology leadership roles.