CS210 : Scientific Computing

Fall 2020

Lectures: TuTh, 12:30 PM - 01:50 PM, Zoom meeting link available on ilearn.
Professor: Tamar Shinar (shinar@cs.ucr.edu)
Professor Office hours: Thursdays, after class
TA: Uday Singh Saini (usain001@ucr.edu)
TA Office hours: Thursdays, 3-5pm
Piazza: CS 210 Piazza page (Signup: link)

Textbook (recommended): Linear Algebra and Learning from Data, by Gilbert Strang
Other resources:
Scientific Computing, An Introductory Survey, by Michael T. Heath
Numerical Algorithms, by Justin Solomon
Numerical Optimization, by Jorge Nocedal and Stephen J. Wright (available online)
Scientific computing an introduction using Maple and MATLAB, by Walter Gander and Felix Kwok (available online)
Numerical Linear Algebra, by David Bau III and Lloyd N. Trefethen


This course provides an introduction to key concepts and methods in scientific computing, including numerical linear algebra, solution of linear and non-linear systems of equations, and optimization. The goal is to prepare you to use scientific computing in your area (e.g. graphics, vision, robotics, machine learning, data mining, etc.) or to continue on to further study of special topics in scientific computing.


Homework will be weekly (with exceptions) and should be completed individually.
The midterm will cover the material in lectures 1-9 and homeworks 1-5.
The final will cover the material in lectures 10-17 and homeworks 6-9.
No notes, calculators, or other devices are allowed during exams.


The lowest homework grade will be dropped in computing your total homework score.

Late Hours. Each student has 48 late hours to use over the course of the quarter for homework submission. Within those 48 hours, there is no penalty for late submission. Beyond the 48 hours, late homework may be submitted up to the time solutions are posted, for a penalty of -10%/day.

Exceptions. Please email the professor directly if there are any extenuating circumstances related to homework deadlines or exams.