Computational methods for solving numerical problems in science, engineering and business. Linear and non-linear equations, approximation, optimization, interpolation,integration and differentiation. The aim is to give students a basic understanding of floating-point arithmetic and the implementation of algorithms used to solve numericalproblems, as well as a familiarity with current numerical computing environments.Course concepts are crucial to a wide range of practical applications such as computational finance and portfolio management, graphics and special effects, data mining and machine learning, as well as robotics, bioinformatics, medical imaging and others.
See the Syllabus for more information.
Course Staff and Contact
Instructor: Lisa Zhang
Office Hours: MF11:00-12:00, W13:00-14:00
Email: lczhang [at] cs [dot] toronto [dot] edu
Teachin Assistants: Vlad, Hossein
Please include "CSC338" in your subject.
All announcements will be made on Piazza and Quercus
Michael Heath, Scientific Computing: An Introductory Survey, Second Edition, McGraw Hill, 2002.
Roughly the first half of the book will be covered. The relevant chapters have been made available by McGraw Hill in the textbook store at a special price.
The course schedule is tentative and subject to change.
|Week 1||Jan 7||Lecture|
|Week 2||Jan 14||Lecture|
|Homework 1 (Jan 21 9pm)|
|Week 3||Jan 21||Lecture|
|Week 4||Jan 28||Lecture|
|Homework 2 (Feb 4 9pm)|
|Week 5||Feb 4||Lecture|
|Week 6||Feb 11||Lecture|
|Week 7||Feb 25||Lecture|
|Homework 3 (Mar 4 9pm)|
|Week 8||Mar 4||Lecture|
|Week 9||Mar 11||Lecture|
|Homework 4 (Mar 18 9pm)|
|Week 10||Mar 18||Lecture|
|Week 11||Mar 25||Lecture|
|Homework 5 (Apr 1 9pm)|
|Week 12||Apr 1||Lecture|