What are good second course books in linear algebra for self-study?

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SUMMARY

The discussion focuses on recommended second course books for self-study in linear algebra, specifically for undergraduate students. Key titles mentioned include "Linear Algebra Done Right" by Sheldon Axler, which emphasizes a conceptual approach by delaying the introduction of determinants, and "Algebra" by Michael Artin, which integrates determinants early in the text. Additionally, "Linear Algebra" by Serge Lang and "Linear Algebra" by Friedberg, Insel, and Spence are highlighted as valuable resources, with the latter offering a more traditional perspective.

PREREQUISITES
  • Familiarity with basic linear algebra concepts and terminology.
  • Understanding of undergraduate-level mathematics.
  • Experience with self-study techniques and resources.
  • Knowledge of different pedagogical approaches to mathematics education.
NEXT STEPS
  • Explore "Linear Algebra Done Right" by Sheldon Axler for a conceptual understanding of linear algebra.
  • Study "Algebra" by Michael Artin to gain insights into the use of determinants in modern algebra.
  • Read "Linear Algebra" by Friedberg, Insel, and Spence for a standard approach to the subject.
  • Investigate supplementary resources or problem sets to reinforce concepts from these texts.
USEFUL FOR

Students pursuing undergraduate mathematics, self-learners in linear algebra, and educators seeking effective teaching materials for advanced linear algebra courses.

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What are best second course(undergraduate) books in linear algebra for self-study?I have already read Introduction to Linear Algebra by Lang.
 
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Linear Algebra Done Right. You can use it in conjunction with Artin: Algebra (I mentioned this to you before...).

Axler avoids determinants till the end, but Artin uses Determinants in chapter 1. However, Artin is a Modern Algebra book...

You could always read Lang's Linear Algebra. However, I really enjoy Axler.

Another book that is popular is Friedberg/Insel/Spence. It takes a more standard approach.
 

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