COURSE CURRICULUM

The Bachelor of Science in Artificial Intelligence at RIT is a structured four-year program designed to build strong foundations in computing, mathematics, psychology, and advanced AI systems while integrating extensive hands-on learning and interdisciplinary study. In the first year, students are introduced to programming, AI fundamentals, calculus, writing, and general education subjects, including global perspectives and psychology, which help them understand both technical and human-centered aspects of computing. The second year strengthens core skills through courses in software development, discrete mathematics, probability and statistics, software engineering, cognitive psychology, and introductory artificial intelligence, along with technical communication, human-centered computing, and linear algebra. This year also includes preparation for cooperative education experience and foundational AI law concepts.In the third year, students transition into advanced AI topics such as machine learning, optimization algorithms, visual analytics, interactive machine learning, reinforcement learning, and database systems, along with courses in language technology and large language models. Students also complete immersion courses and open electives while gaining real-world experience through a required AI co-op. The fourth year focuses on specialized and advanced areas including AI security, concurrent and distributed AI systems, and AI electives that allow students to tailor their expertise. Students also complete a capstone project that integrates technical knowledge, teamwork, and applied AI problem-solving in real-world scenarios.Overall, the program totals 122 credit hours and combines strong theoretical foundations with practical experience in cutting-edge AI technologies. It prepares students for careers in machine learning engineering, AI development, robotics, natural language processing, data science, cybersecurity, and research. Graduates gain the ability to design, build, and manage intelligent systems while addressing ethical, legal, and technical challenges in modern AI applications.