CSCI 0530 - Directions: The Matrix in Computer Science

Institution:

Brown University

Subject:

Description:

The aim of this course is to provide students interested in computer science an introduction to vectors and matrices and their use in modeling and data analysis. Students will study (1) concepts and proofs in linear algebra, (2) data-analysis techniques such as principal component analysis, latent semantic indexing, and linear regression, and (3) applications of these techniques to computer science. Example applications: transformation of shapes, detecting faces in images, error-correcting codes, factoring integers, categorizing new stories, and Google's method for ranking web pages. This course satisfies the linear algebra requirement for the Computer Science Sc.B. Prerequisites: No formal prerequisites, but students are expected to be comfortable with mathematics and with computing.

Credits:

0.00 - 1.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.brown.edu

Phone Number:

(401) 863-1000

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Semester

The Course Profile information is provided and updated by third parties including the respective institutions. While the institutions are able to update their information at any time, the information is not independently validated, and no party associated with this website can accept responsibility for its accuracy.