What topics are covered in linear algebra class?

[Saurophaganax]

What topics/chapters are covered in a typical linear algebra class? I am a physics/math major but I won't be able to take classes for a few years. I am trying to teach myself linear algebra so I can read physics textbooks. Thanks

 

[Fredrik]

This is what I said to someone who asked about what he should know before he studies quantum mechanics.

The concepts from linear algebra that you need to understand are: vector spaces, inner products, linear independence, orthonormal bases, linear operators, matrix multiplication, the relationship between linear operators and matrices, the adjoint operation, eigenvectors and eigenvalues.

I should have mentioned determinants as well. If you understand these things, you're off to a good start. I've been told that Friedberg, Insel & Spence is a very nice book. Axler is also good. There are several other acceptable choices. I would however recommend that you stay away from books like Anton, which wait as long as possible with the introduction of linear operators (also called linear maps, linear functions or linear transformations). The sooner they are introduced, the better.

 

[bcrowell]

This is the best linear algebra book I know of, and it also happens to be free: Hefferon, http://joshua.smcvt.edu/linalg.html/ . "Best" for me means interesting applications and good motivation for new topics as they're introduced.

 

[mathwonk]

here are at least two free linear algebra books:

http://www.math.uga.edu/~roy/look for the free notes.

#1) is a 15 page linear algebra book covering everything in basic linear algebra excelt determinants.

#7) covers even that, and much more in more detail in less than 100 pages.

If you are picky and want a really good book, here is one 250 pages long by Sergei Treil:

http://www.math.brown.edu/~treil/papers/LADW/LADW.pdf

 

[moskva]

This is the best linear algebra book I know of, and it also happens to be free: Hefferon, http://joshua.smcvt.edu/linalg.html/ . "Best" for me means interesting applications and good motivation for new topics as they're introduced.

Sorry to get off topic, but...

Thank you sooooo much! I've been trying to understand the concept of a vector space for the past week and a half. This has been the best explanation to me so far! Thanks!