The CSRC strives to promote development and advancement in the interdisciplinary subject of computational science, as well as the creation and implementation of innovative university curricula and training programs. This is accomplished by fostering research, developing educational programs, and promoting industrial interaction, outreach, and partnership activities.

The Advanced Certificate in Professional Computational Science is designed to provide knowledge for private and public industry professionals as well as graduate students who wish to learn professional and technical computational skills in their fields. Skills include: use of tools available for scientific applications development, scientific visualization, database query, simulation and modeling packages, computational templates such as Matlab® and Maple,® and the choice of appropriate hardware resources for different classes of problems.

Courses are taught online to provide the flexibility necessary for the student’s other professional and personal commitments. Students are normally enrolled in no more than two online courses at one time.

Credit earned through the Computational Science Certificate program can be applied toward the units required to obtain the Master of Science in Computational Science with concentration in Professional Applications degree (PSM). If you wish to apply for the Master’s degree, you must fill out an application through SDSU’s Graduate Admissions office.

In order to earn an advanced certificate or master's degree, you must apply and be admitted to SDSU. You may not take more than 9 units prior to being officially admitted into the advanced certificate or master's degree program if you wish to earn an official SDSU advanced certificate or degree. For more information, please contact the Division of Graduate Affairs at gra@mail.sdsu.edu or call (619) 594-5213.

Questions about the Computational Science Certificate?
Email compsci@myth.sdsu.edu or call (619) 594-3430.

COMP 526 - Computational Methods for Scientists
This course is designed to be self-contained and suitable for students with varied technical backgrounds. The course teaches programming in variety of contexts: C-language, Fortran 90, and Perl, giving the student a background for code development appropriate to many scientific disciplines. Additional topics may include dynamic html programming: CGI for the World Wide Web, and an introduction to MPI for parallel computing.

COMP 589 - Computational Imaging
Topics Include: Cognitive principles governing effective design and analysis of data representations; design strategies for enhancing dimensionality and information density of visual portrayals of information; software tools for visualization; modern image analysis, and interface propagation techniques with an emphasis on implicit representation.

COMP 601 - Business Skills for the Information Age
Introduction to some key science and technology related skills that businesses value in employees. Topics introduced in this course include: effective communication tools; organizational tools and an analytical tools overview.

COMP 696 - Basic Computational and Applied Statistics
Statistical tools for basic analysis. Topics include: Variation and understanding its importance in decision making, selected graphical tools, descriptive statistics, basic distributions,and inferential statistics.