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Category: Tutorial

**Math Tutor DVD - Linear Algebra Vol 2 (2014) [21 flv] | 938MB**

The Linear Algebra Tutor - Vol 2

- 5 Hour Course

Learn with Step-by-Step Video Lessons.

Eigenvectors, Linear Independence, Determinants, and more.

Gain Practice and Confidence by solving Problems.

Sect 1: Transformation Matrices for Scaling

Sect 2: Transformation Matrices for Rotation

Sect 3: Transformation Matrices for Translation

Sect 4: The Rank of a Matrix

Sect 5: Finding the Determinant of a Matrix by Row Operations - Part 1

Sect 6: Finding the Determinant of a Matrix by Row Operations - Part 2

Sect 7: Finding the Determinant of a 3x3 Matrix - Fast Method

Sect 8: Find the Cross Product of Two Vectors using Determinants

Sect 9: Cofactors of a Matrix

Sect 10: Finding the Determinant with Cofactors

Sect 11: Adjoints and Inverses

Sect 12: Important Properties of Determinants

Sect 13: Linear Independence and Basis

Sect 14: Motivation for Eigenvalues and Eigenvectors

Sect 15: The Eigenvalue Problem

Sect 16: Finding Eigenvalues - Part 1

Sect 17: Finding Eigenvalues - Part 2

Sect 18: Finding Eigenvalues - Part 3

Sect 19: Finding Eigenvalues - Part 4

Sect 20: Finding Eigenvectors - Part 1

Sect 21: Finding Eigenvectors - Part 2

Detailed Description

Linear Algebra is a course that is usually taken by Sophomore or Junior students in Engineering, Science, and Mathematics. There are a vast array of topics in Linear Algebra that will be of practical use to all students as they learn to solve real-world problems in more advanced classes.

This course continues the study of Linear Algebra where Volume 1 ended and teaches all topics with step-by-step examples. First, we introduce the concept of a transformation matrix and study transformation matrices for scaling, rotation, and translation of 2D objects.

Next, we study the concept of the Rank of a Matrix and learn how to find the determinant of any size matrix using row reduction techniques. We then learn an alternative technique for finding the determinant that involves matrix cofactors.

We conclude the course with an extensive discussion of eigenvalues and eigenvectors with numerous examples to give the student practice.

The easiest way to learn this material is through step-by-step video lessons!

Uploaders Note

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