Computational Science is the third  branch of science. It is a marriage of the experimental and theoretical, combining modeling and programming to test scientific hypotheses. Techniques and skills in data analysis, algorithmic design and implementation, and mathematical  modeling are fundamental  in the discipline. Increasingly in modern scientific research, doing exploratory computational  work prior to actual laboratory experimentation is common, both as a time and money-saver. In health-related areas, dealing successfully with massive amounts  of data in different formats is a critical hurdle toward effective and efficient care.

Learning Outcomes for Computational Science

Upon completion of the major and degree requirements  the successful graduate will have:

1. a robust understanding of the three broad areas that comprise computational science:
a. Data processing and analysis
b. Algorithmic design, analysis, and implementation c. Mathematical modeling and analysis;
2. the ability to work independently  to effectively describe a problem within a computational  science framework, and create and implement a plan to solve that problem;
3. understanding of the interdisciplinary  nature of computational  science, and being able to solve, computationally,  problems in an chosen related major/minor  discipline;
4. an understanding and appreciation of the historical development of computation  and the role of computational  science in modern applications within data-dependent disciplines.