course in linear algebra
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course in linear algebra by David B. Damiano

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Published by Harcourt Brace Jovanvich in San Diego .
Written in English


  • Algebras, Linear.

Book details:

Edition Notes

Includes index.

StatementDavid B. Damiano, John B. Little.
ContributionsLittle, John B.
LC ClassificationsQA184 .D35 1988
The Physical Object
Paginationxiii, 434 p. :
Number of Pages434
ID Numbers
Open LibraryOL2415993M
ISBN 100155151347
LC Control Number87081875

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  No headers. This text, originally by K. Kuttler, has been redesigned by the Lyryx editorial team as a first course in linear algebra for science and engineering students who have an understanding of basic algebra. All major topics of linear algebra are available in detail, as well as proofs of important theorems.   This book is the text for Massachusetts Institute of Technology’s Linear Algebra course , whose goals are “using matrices and also understanding them.” There’s enough material in the book for a year-long course, and the MIT course covers primarily the first seven chapters. Most students taking a course in linear algebra will have completed courses in di erential and integral calculus, and maybe also multivariate calculus, and will typically be second-year students in university. This level of mathematical maturity is expected, however there is little or no requirement to know calculus itself to use this book File Size: 2MB. Welcome to Linear Algebra for Beginners: Open Doors to Great Careers! My name is Richard Han. This is a first textbook in linear algebra. Ideal student: If you're a working professional needing a refresher on linear algebra or a complete beginner who needs to learn linear algebra for the first time, this book .

vector spaces, linear maps, determinants, and eigenvalues and eigenvectors. Anotherstandardisthebook’saudience: sophomoresorjuniors,usuallywith a background of at least one semester of calculus. This is a good contemporary book on linear algebra. It would be appropriate for any sophomore-level linear algebra course for pure math, applied math, CS, or related fields. It includes some nice sections on computing that could lead naturally into a course on numerical methods. Clarity rating: 5 Author: Jim Hefferon.   Course description. This course covers the following topics: solving systems of linear equations; matrices and linear transformations; image and kernel of a linear transformation; matrices and coordinates relative to different bases; determinants; eigenvalues and eigenvectors; discrete and continuous dynamical systems; least-squares approximation; applications, differential equations, and. Every time I’ve taught the course (undergraduate), I’ve been saddled with someone else’s choice of text. And they’ve generally been isomorphic (the same) and not particularly inspiring. So I’m going with speculation here - in terms of what I think.

This book is especially suited to a second course in linear algebra that emphasizes abstract vector spaces, although it can be used in a first course with a strong theoretical emphasis. Updates to the 5th Edition include revised proofs of some theorems, additional examples, and new exercises. Also new in this revision are online solutions for. Course Highlights. This course parallels the combination of theory and applications in Professor Strang’s textbook Introduction to Linear Algebra. The course picks out four key applications in the book: Graphs and Networks; Systems of Differential Equations; Least Squares and Projections; and Fourier Series and the Fast Fourier : Prof. Gilbert Strang. A First Course in Linear Algebra is an introductory textbook aimed at college-level sophomores and juniors. Typically students will have taken calculus, but it is not a prerequisite. The book begins with systems of linear equations, then covers matrix algebra, before taking up finite-dimensional vector spaces in full generality. The final chapter covers matrix representations of linear.   What this book is: This "textbook" (+videos+WeBWorKs) is suitable for a sophomore level linear algebra course taught in about twenty-five lectures. It is designed both for engineering and science majors, but has enough abstraction to be useful for potential math majors. Our goal in writing it was to produce students who can perform computations with linear systems and also understand the.