CSCI 2227 Introduction to Scientific Computation
An introductory course in computer programming for students interested in numerical and scientific computation. Students will learn to write their own computer programs that solve computational problems such as interpolating data, solving nonlinear equations, and simulating differential equations. Emphasis will be placed on the underlying computation methods, precision, and potential sources of numerical error, including the mechanics of 64-bit floating-point numbers. Topics include Taylor approximations, interpolatory quadrature, Newton's Method, Gaussian Elimination, and Runge-Kutta recurrences, with more as time allows. Basic Calculus knowledge is required (polynomials, derivatives, and integrals), and familiarity with infinite series is recommended. Students will write programs in the Python programming language. No prior Python experience assumed.
Course overview
- Department
- Computer Science
- School
- MCAS
- Credits
- 3
- Level
- Undergraduate
- Offered
- Periodically
Catalog details
- Prerequisites
- MATH1101 or MATH1102
Requirements fulfilled
- Computer Science B.A.: CSCI 2000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
- Neuroscience B.S.: Computation (6 Credits) — Any one of the following courses (Current University Catalog; students should confirm their catalog year)
- Applied Physics B.S.: Corequisite: Computer Science (one course) (Current University Catalog; students should confirm their catalog year)
- Physics B.S.: Corequisite: Computer Science (one course) (Current University Catalog; students should confirm their catalog year)
- Mathematics B.S.: Natural science, computer science, or economics corequisites (Current University Catalog; students should confirm their catalog year)
Official evaluation summary
Data freshness
Instructors
Sections
- Section 01