M.S. Computational Science

The Master of Science in Computational Science (CSCI) enables those students who already hold a B.S. degree in science, engineering, or another appropriate discipline to gain advanced knowledge and research experience that are needed for them to become successful computer or computational scientists. The program will endeavor to produce graduates who possess the deeper knowledge and skills in mathematics and computing that will allow them to participate in the extension of scientific thought and knowledge at an advanced level. 

Program Goals

  • Offer students advanced training in computing and significant exposure to other science and engineering fields.
  • Prepare students for careers in broad areas that require extended proficiency in programming, modeling, computing, and software system management.
  • Foster a cutting-edge practice for the process of how Mathematics, Computer Science and other areas of science and engineering would integrate meaningfully and impact our everyday lives and the future of the natural world.
  • Provide much needed opportunities for interaction with the local citizenry concerning advancing computer and/or computing technologies through formal classroom instruction, internships, seminars and informal educational opportunities at local events. 

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  • General Information
  • Degree Requirements
  • Course List
  • FAQs

CS Masters Degree


USCB offers the Master of Science with a major in Computational Science. To qualify for graduation, a minimum of 30 credit hours must be completed according to the requirements below.

Also, please note the following stipulations regarding transfer of credits from another institution:

  • Only courses with grades of B or better may be transferred from another institution into the program. Course work transferred for credit toward the MS CSci degree must be from an accredited institution and must be no more than six years old at the time of graduation.
  • Course work transferred from another institution must be relevant to the program and have course content and a level of instruction equivalent to that offered by the University’s own graduate program.

I. Mathematics and Statistics (3 hours)

  • CSCI B501/STAT B501 - Advanced Statistical Methods

II. Core Courses (12 hours required)

Complete all of the following:

  • CSCI B500 - Practical Computing for Computational Scientists (3 hours)
  • CSCI B502/MATH B502 - Numerical Analysis for Computing (3 hours)
  • CSCI B550 - Systems Modeling and Simulation (3 hours)
  • CSCI B569 - High Performance Computing (3 hours)

III. Electives (9 hours required)

Choose from the following:

  • CSCI B515 - Topics in Computational Science (3 hours)
  • CSCI B516 - Data Communications and Networking (3 hours)
  • CSCI B520 - Advanced Topics in Database Systems (3 hours)
  • CSCI B522 - Data Mining (3 hours)
  • CSCI B563 - Digital Image Processing (3 hours)
  • CSCI B566 - Data Visualization (3 hours)
  • CSCI B570 - Software Systems Design and Implementation (3 hours)
  • CSCI B599 - Independent Study (1-3 hours)
  • CSCI B601 - Principles of Computer Security (3 hours)
  • CSCI B622 - Data Management and Analytics (3 hours)
  • CSCI B699 - Industrial or Research Internship (1-3 hours)

IV. Thesis, Project, or Coursework Option (6 hours required)

Choose one of the following:

  • Project Option: CSCI B797 - Research Project (3-6 hours)


  • Master's Thesis Option: CSCI B799 - Master's Thesis (3-6 hours)


  • Coursework Option:  Take an additional 3 hours of CSCI elective coursework at the 500 level or above, plus one of the following:

     CSCI B599 (Independent Study)
     CSCI B699 (Industrial or Research Internship)


Computer / Computational Science (CSCI) Graduate Courses

CSCI B500 – PRACTICAL COMPUTING FOR COMPUTATIONAL SCIENTISTS (3). (Prereq: Enrollment in CSCI M.S. program OR consent of instructor) Application of mathematical, science, and engineering problems to software engineering. Introduction to operating systems including UNIX/LINUX.

CSCI B501 (STAT B501) – ADVANCED STATISTICAL METHODS (3). (Prereq: STAT B340 or consent of instructor) Methods of data description and analysis, regression and spectral techniques, graphical presentation, estimation and forecasting. Statistical software will be used throughout the course.

CSCI B502 (MATH B502) – NUMERICAL ANALYSIS FOR COMPUTING (3). (Prereq: CSCI B280 and MATH B240, or consent of instructor) Application of tools and techniques to algorithmic problems arising in discrete applied math. Topics include probabilistic methods, entropy, linear algebra methods, risk analysis, approximation and optimization techniques, and performance analysis.

CSCI B515 – TOPICS IN COMPUTATIONAL SCIENCE (3).(Prereq: undergraduate programming experience or CSCI B500 or consent of instructor) Selected topics in computational science.

CSCI B516 – DATA COMMUNICATIONS AND NETWORKING (3). (Prereq: undergraduate programming experience or CSCI B500 or consent of instructor) Advanced topics in data communications, architecture, communication protocols, topologies, network access control, LANs, MANs, and WANs; internetworking.

CSCI B520 – ADVANCED TOPICS IN DATABASE SYSTEMS (3). (Prereq: CSCI B320, or consent of instructor) Advanced data-processing techniques, software, database design, implementation, and manipulation.

CSCI B522 – DATA MINING (3). (Prereq: CSCI B501 and CSCI B502) Concepts, issues, tasks and techniques of data mining. Topics include data preparation, feature abstraction, association, classification, clustering, evaluation and validation, scalability, spatial and sequence mining, and data mining applications.

CSCI B550 - SYSTEMS MODELING AND SIMULATION (3). (Prereq: {CSCI B500, CSCI B501, and CSCI B502} or consent of instructor) Introduction of computational tools, models, system dynamics, input and output analysis, and performance analysis.

CSCI B563 – DIGITAL IMAGE PROCESSING (3). (Prereq: CSCI B500, CSCI B501, and CSCI B502) Computational techniques in image processing and analysis.

CSCI B566 – DATA VISUALIZATION II (3). (Co-requisites: {CSCI B500 and CSCI B501} or consent of instructor) Advanced techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science.

CSCI B569 – HIGH PERFORMANCE COMPUTING (3). (Co-requisite: CSCI B502 or consent of instructor and Prerequisite: {CSCI B500 and CSCI B501} or consent of instructor) Introduction of the design, analysis, and implementation of high performance computational science and engineering applications using advanced computer architectures, parallel algorithms, parallel languages, and performance-oriented computing facilities.

CSCI B570 – SOFTWARE SYSTEMS DESIGN AND IMPLEMENTATION (3). (Prereq: CSCI B500 or consent of instructor) Techniques involved in the planning and implementation of real-life software systems. Topics include software planning, design, implementation, testing, and documentation.

CSCI B599 – INDEPENDENT STUDY (1-3). Research under the supervision of a faculty member.

CSCI B601 – PRINCIPLES OF COMPUTER SECURITY (3). (Prereq: CSCI B201 or consent of instructor) Principles and practices of computer system security including operating system security, network security, software security and web security.

CSCI B622 – DATA MANAGEMENT AND ANALYTICS (3). (Prereq: CSCI B520 or consent of instructor) Foundations of data analytics. Concepts and skills for relational data modeling, querying, and management.

CSCI B699 – INDUSTRIAL OR RESEARCH INTERNSHIP (1-3). Practical full-time work experience in an area of Computational Science, selected by the student and approved by the Department Chair or Computational Science Program Coordinator.

CSCI B797 – RESEARCH (3-6). Research in computational science.

CSCI B799 – THESIS OR PROJECT (3-6). Preparation of a project or thesis for the master's degree.

  1. An application for admission
  2. Official scores from the general Graduate Record Examination (GRE). Exemptions: 1 - The GRE may not be required for students who have been working in Computer/Computational Science fields for two or more years and can provide verification of employment. 2 - The GRE is not required for USCB graduates.
  3. Official college transcripts of all prior academic work, with a minimum cumulative GPA of 3.0 on a 4.0 scale.
  4. Two letters of recommendation, preferably from current/prior professors or supervisors
  5. A résumé or CV (curriculum vitae) listing relevant work experience, publications, and projects
  6. International Applicants who have completed university-level coursework, outside of the United States will need to have a course-by-course evaluation of transcripts completed and forwarded to the University of South Carolina Beaufort by a service, which may include one of the following or a service that is certified by the National Association of Credential Evaluation Services (NACES) or the American Translators Association (ATA):

    World Education Services, Inc.
    Phone: 212-966-6311
    Fax: 212-966-6395
    Email: info@wes.org
    Educational Credential
    Evaluators, Inc.
    Phone: 414-289-3400
    Fax: 414-289-3411
    Email: eval@ece.org

    Educational Credential
    Evaluators, Inc.
    Phone: 414-289-3400
    Fax: 414-289-3411
    Email: eval@ece.org

    Josef Silny & Assoc., Inc.
    International Education Consultants
    Phone: 305-273-1616
    Fax: 305-273-1338
    Email: info@jsilny.com


    Email: Contact Form

  7. For applicants from non-English speaking countries Test of English as a Foreign Language (TOEFL) scores (550 on the standard, 213 on the computer-based version or 77 on the internet based TOEFL) are required. OR send official IELTS test score. IELTS scores for admissions requires at least a 6.0. These tests is required for all international students except those whose native language is English. Please note: the following countries are exempt from the TOEFL requirement: American Samoa, Australia, Bahamas, Barbados, Belize, Canada (Quebec students must take the TOEFL), Dominica, Grenada, Grand Cayman, Guyana, Ireland, Liberia, New Zealand, Sierra Leone, Trinidad/Tobago, and United Kingdom.
  8. For students who lack the content prerequisites required for the program upon admission, additional requirements may be necessary to ensure student success. These requirements include, but not limited to, retaking undergraduate courses requiring better performance, taking remedial course work in specified areas (which may not necessarily count towards graduation requirements), or completing special projects to develop and/or improve skills required by the program. These additional requirements will be finalized on a case-by-case basis.
Graduate Semester
(per credit hour)
(per credit hour)
Resident Tuition $6,867.00 $572.25 $13,734.00 $1,144.50
Non-Resident Tuition $14,880.00 $1,240.00 $29,760.00 $2,480.00
Technology Fee $168.00 $14.00 $336.00  
Parking & Security ** $25.00 $25.00 $50.00  
Estimated Resident Tuition & Fees * $7,060.00   $14,120.00  
Estimated Non-Resident Tuition & Fees * $15,073.00   $30,146.00  

*Tuition and fees listed are for school year 2020-21 are subject to change without notice. Tuition and fees have not yet been established for 2021-2022. Estimate does not include the cost for books and supplies, and other miscellaneous fees that are course-specific fees. The complete tuition and fee schedule is available at https://www.uscb.edu/bursars/paying_tuition_fees/tuition_fees.html

** $25 each Fall & Spring, $15 each Summer Session

***Newly admitted student will pay a one-time New Student Fee and a one-time Matriculation fee.

  1. Develop scientific programs in a high-level language such as Java, C/C++, or Python.
  2. Use scientific computational/modeling tools such as MATLAB.
  3. Demonstrate substantive knowledge and skills in a chosen area of computational problem-solving.
  4. Identify and apply methods to efficiently manage data across disciplines.
  5. Apply critical thinking skills to develop computer simulations and models and solve problems with minimal guidance.
  6. Work fluently with concepts such as numerical methods and computing techniques/theories to solve problems in an application area.
  7. Communicate technical concepts and results to both specialist and non-specialist audiences, in the form of written technical reports, research theses, scholarly articles, and/or oral presentations.
  8. Students will gain knowledge of the literature of the discipline and will be engaged in research and/or appropriate professional practice and training.

On-campus housing will be available for graduate students. However, we presently do have not have on-campus housing facilities for families with children.

Yes, selected students will receive graduate assistantships -- detailed information coming soon.

Year 1

Fall Semester
  • CSCI B501/STAT B501 (3 hrs)
  • CSCI B500 (3 hrs)
  • CSCI Elective (3 hrs)
Spring Semester
  • CSCI B502/MATH B502 (3 hrs)
  • CSCI B569 (3 hrs)
  • CSCI Elective (3 hrs)
Summer Session
  • CSCI B699 (1-3 hrs)

Year 2

Fall Semester
  • CSCI B550 (3 hrs)
  • CSCI B797 (3-6 hrs) - for students in Project option
    CSCI B799 (3-6 hrs) - for students in Thesis option
    CSCI B599 (3 hrs) or B699 (3 hrs) or Elective (3 hrs) - for students in Coursework option
Spring Semester
  • CSCI Elective (3 hrs)
  • CSCI B797 (3-6 hrs) - for students in Project option
    CSCI B799 (3-6 hrs) - for students in Thesis option
    CSCI B599 (3 hrs) or B699 (3 hrs) or Elective (3 hrs) - for students in Coursework option
Summer Session
  • CSCI B699 (1-3 hrs)

Yes, new M.S. students may begin their graduate studies in either the fall or spring semester of a given academic year, though beginning in the fall is preferable mainly due to the timing of first-year course offerings, many of which have prerequisites and corequisites.

Yes -- selected core courses and electives will be offered during the summer months.

Class sizes will typically be small -- often less than 20 students.

In order to ensure small class sizes and appropriate individual attention is given to each student, we expect to have a maximum of 20 (twenty) graduate students enrolled in the M.S. program per year.

Please contact Dr. Brian Canada, Associate Professor of Computational Science and Chair of Computer Science, at 843-208-8314, or by email at bcanada@uscb.edu.


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