COURSE CURRICULUM

The M.S. in Computer Science at UNH is structured as a flexible graduate program designed to match different student goals through three pathways: thesis, project, and course-only options, each requiring a combination of advanced coursework and a graduate seminar (CS 900). Across all options, students complete a set of graduate-level CS courses—typically between seven and ten depending on the track—covering at least 30 credits overall, with requirements ensuring academic depth, implementation experience, and exposure to advanced theory and systems. In the thesis option, students complete seven graduate courses plus a six-credit Master’s Thesis (CS 899), working closely with a faculty advisor and a committee of at least three members to produce original research. The project option replaces the thesis with a three-credit Master’s Project (CS 898), focusing more on applied problem-solving and practical system development, while the course option emphasizes broader coursework without a formal thesis or project, requiring ten graduate courses for a more comprehensive academic experience. All students must meet shared requirements, including at least two implementation-intensive courses chosen from subjects such as compiler design (CS 812), systems programming (CS 820), artificial intelligence (CS 830), parallel and distributed programming (CS 835), neural networks (CS 852), information retrieval (CS 853), computer graphics (CS 870), or data science for knowledge graphs and text (CS 881). In addition, students must take either algorithms (CS 858) or formal verification (CS 845), ensure that at least three courses are at the 900 level, and study under at least five different faculty members, promoting academic diversity. The program also requires public presentation of capstone work, which may be part of a course or independent study. Overall, the structure balances theoretical foundations, advanced computing topics, and hands-on implementation, preparing graduates for roles in software engineering, artificial intelligence, data science, systems development, and research-driven careers in computing.