The Accelerated Bachelor’s degree/Master of Science in Computational and Data Sciences program is a unique opportunity open to all Chapman University undergraduates with a strong mathematical and/or computational background. Undergraduates will have the opportunity to obtain a Bachelor’s degree of their choice and a CADS M.S. with just one additional year of study.
An undergraduate degree specifically in computational science is not required for admission. The program will consider applicants from a broad range of undergraduate science disciplines (e.g. biology, chemistry, computer science, biochemistry and molecular biology, mathematics, physics, economics) as long as they satisfy the prerequisites for the program and meet admission requirements.
Chapman students should apply to the graduate program in their junior year, prior to taking graduate level courses. Students will receive conditional admission to the program, pending completion of their bachelor’s degree as stipulated in the graduate catalog (see explanation of conditional admission in the graduate catalog). If accepted into the graduate program, undergraduate students may take up to 15 graduate credits once they have completed a minimum of 90 undergraduate credits have been completed or will be completed prior to start of the course in order to enroll in a graduate course. These 15 credits may also count towards the undergraduate degree credit requirement (please check with your major advisor). Students will be officially admitted to the M.S. to complete their graduate coursework after receiving their undergraduate degree. The application process, prerequisites, and graduate program requirements are as specified for the M.S. in Computational and Data Sciences ; however, the application fee and GRE are waived.
Students who have taken both CPSC 392 and CPSC 393 will take CS 613 , instead of CS 530 , as a core course.
Chapman Prerequisites:
- Differential Equations (MATH 315 or MATH 350)
- Computer Science (CPSC 230, CPSC 231 & CPSC 350)
- Probability and Statistics (MATH 360 & MATH 361)