COURSE CURRICULUM

The Master of Science in Artificial Intelligence (MSAI) is a 33-unit graduate program designed to provide advanced training in AI, machine learning, and data-driven systems. The program begins with 9 units of core courses that establish a strong foundation in artificial intelligence, machine learning, and mathematical methods for data and decision sciences. These include courses in AI and data engineering, machine learning, and mathematical foundations, ensuring students develop essential theoretical and technical skills.Students then complete 6 units of specialization courses by choosing either the Data Science or Autonomous Systems track. The Data Science specialization includes courses such as data mining, recommender systems, and natural language processing, while the Autonomous Systems specialization focuses on intelligent autonomous systems, deep learning, and reinforcement learning. This structure allows students to gain focused expertise in a specific area of AI aligned with their career goals.In addition, students complete 9 units of elective courses, selecting three courses from approved lists. At least one course must be from a primary technical area (Area A), while the remaining courses can be chosen from either Area A or additional approved technical electives (Area B). This flexibility allows students to broaden their knowledge across AI-related domains. The program also requires completion of a 3-unit Graduate Writing Assessment Requirement (GWAR), typically fulfilled through a seminar or engineering writing course.The program concludes with a 6-unit culminating experience, where students choose between a thesis or a project. The thesis option involves original research under faculty supervision, while the project option focuses on applied development work, often contributing to larger team-based systems. Overall, the 33-unit structure ensures a balance between theoretical knowledge, technical specialization, and practical application, preparing graduates for advanced roles in artificial intelligence, machine learning, and intelligent systems development.