The University of South Carolina Beaufort M.S. in Computational Science is a strong fit for this directory because the program combines advanced computing with modeling, data analysis, scientific visualization, high-performance computing, and machine learning. The 30-credit degree is intended for students with backgrounds in science, engineering, computer science, mathematics, and related technical fields.
USCB gives students unusual flexibility in how they complete the degree. Instruction is available 100% online, in a blended format, or in person, and students may begin in the fall or spring. The university also offers thesis, project, and coursework completion options.
USCB Computational Science Program Overview
| Degree | M.S. in Computational Science |
| Credits | 30 |
| Format | Online, blended, or campus-based |
| Campus locations | Bluffton and Hilton Head Island, South Carolina |
| Machine learning | Included within the program’s applied computing and data curriculum |
| Completion options | Thesis, project, or coursework |
| Start terms | Fall or spring |
| Minimum published time | As little as 1 year, depending on prior preparation |
USCB describes the degree as preparation for careers that require advanced programming, modeling, computing, and software-system skills. The program is interdisciplinary and applies computational methods across physical, biological, engineering, and other scientific fields.
View the official USCB M.S. in Computational Science program page.
Machine Learning and Data Focus
USCB is broader than a dedicated machine learning master’s, but machine learning is part of the program’s stated academic focus. The university says students gain hands-on experience in machine learning, high-performance computing, scientific visualization, mathematical modeling, simulation, and data analysis.
The elective structure also gives students room to build a data- and machine-learning-oriented plan of study. Relevant options include Data Mining, Digital Image Processing, Data Visualization, Data Management and Analytics, and advanced database coursework. This makes USCB a reasonable option for students who want machine learning skills within a wider computational-science degree.
Curriculum
The M.S. requires 30 graduate credits. The current program structure includes 12 credits of required core coursework, 12 credits of electives, and 6 credits devoted to a thesis, project, or additional coursework option.
Required core courses include:
- CSCI B500 – Practical Computing for Computational Scientists
- CSCI B518 – Numerical and Statistical Methods for Computational Science
- CSCI B550 – Systems Modeling and Simulation
- CSCI B569 – High Performance Computing
Students then select 12 elective credits. Current options include Data Mining, Digital Image Processing, Data Visualization, Advanced Topics in Database Systems, Software Systems Design and Implementation, Principles of Computer Security, Data Management and Analytics, independent study, and an industrial or research internship.
The final 6 credits can be completed through one of three paths:
- Thesis option: complete graduate coursework plus master’s thesis research.
- Project option: complete graduate coursework plus a substantial research or software project.
- Coursework option: complete additional graduate coursework together with an independent study or industrial/research internship.
Review the official USCB degree requirements and course list.
Program Format and Length
Students can choose fully online instruction, blended delivery, or in-person classes. Campus instruction is offered through USCB’s Bluffton and Hilton Head Island locations.
USCB states that the program can be completed in a minimum of one year, depending on a student’s prior academic preparation and study plan. The university also offers an accelerated BS-to-MS path that can allow eligible USCB undergraduates to complete graduate-level coursework before finishing the bachelor’s degree.
Students may start in either the fall or spring semester. USCB also emphasizes small graduate classes, with classes often enrolling fewer than 20 students.
Admissions
Applicants need a bachelor’s degree from an accredited institution. The Computational Science program page lists a minimum cumulative GPA of 3.0 and asks for official transcripts and two letters of recommendation.
USCB’s general graduate admissions page currently says GRE scores are optional. The Computational Science program page still contains older program-specific GRE language and exemptions for some applicants, so prospective students should confirm the current testing requirement with USCB before applying.
The university uses rolling admission for graduate applicants and allows fall or spring entry. Applicants who do not have enough prior coursework in computing, mathematics, or related areas may be required to complete additional preparation.
See current USCB graduate admissions requirements.
Tuition and Cost
USCB’s graduate admissions page lists Computational Science tuition of $572.25 per credit for South Carolina residents and $1,240 per credit for nonresidents. At those published rates, 30 credits would equal about $17,168 in resident tuition or $37,200 in nonresident tuition before required fees and other expenses.
There is an important caveat: the university labels those graduate per-credit figures as rates from the 2021-22 school year. USCB’s 2026-27 general tuition pages publish newer full-time estimates, but they do not clearly provide a current graduate Computational Science per-credit rate. For that reason, students should use the figures above only as a reference and verify their actual rate with USCB before enrolling.
See current USCB tuition and financial aid information.
Career Preparation
The program prepares students for technical roles that combine programming, scientific computing, modeling, simulation, data analysis, and software systems. Possible career directions include computational science, data science, machine learning, scientific software development, high-performance computing, analytics, and research-oriented technical work.
The thesis option is the clearest fit for students considering doctoral study or research careers. The project and coursework options may appeal more to students who want applied experience, including software development, independent study, or an industrial or research internship.
Who Is This Program Best For?
USCB is worth considering if you want a flexible master’s that connects machine learning and data analysis with broader computational methods. The online, blended, and campus choices make the program especially useful for students who want more delivery flexibility than many traditional computational-science degrees provide.
This program is less specialized than a master’s devoted entirely to artificial intelligence or machine learning. It is a better match for students who also want skills in numerical methods, modeling and simulation, high-performance computing, scientific visualization, software systems, and interdisciplinary scientific computing.