Scientific computing studies the world around us. Known and unknown quantities are related through certain rules, e.g. physical laws, formulating mathematical problems. These problems are solved by numerical methods implemented as algorithms and run on computers. The numerical methods are analyzed and their performance (e.g. accuracy, efficiency) studied. Problems, such as choosing the optimal shape for an airplane (to achieve, for example, minimal fuel consumption), finding the fair price for derivative products of the market, or regulating the amount of radiation in medical scans, can be modeled by mathematical expressions and solved by numerical techniques.
Students wishing to study scientific computing should have a strong background in mathematics—in particular calculus of several variables, linear algebra, and statistics—be fluent in programming, and have a good understanding of data structures and algorithm design.
Suggested Related Courses:
- MAT224H1/MAT240H1, MAT244H1, MAT334H1/MAT354H1, MAT337H1/MAT357H1
It is also recommended that students in this focus consider taking a half-course or two from the basic sciences (such as physics, chemistry, biology), as these sciences are the source of many problems solved by numerical techniques.