Difference between revisions of "MAT2233"

From Department of Mathematics at UTSA
Jump to navigation Jump to search
(→‎Topics List: Complete first version of table)
(→‎Topics List: Added sections for each topic and links at the top of the page)
Line 1: Line 1:
 +
 +
A comprehensive list of all undergraduate math courses at UTSA can be found [https://catalog.utsa.edu/undergraduate/coursedescriptions/mat/  here].
 +
 +
The Wikipedia summary of [https://en.wikipedia.org/wiki/Linear_algebra  Linear Algebra and its history].
 +
 
==Topics List==
 
==Topics List==
 
{| class="wikitable sortable"
 
{| class="wikitable sortable"
Line 9: Line 14:
 
||
 
||
  
<div style="text-align: center;">1.1 and 1.2</div>
+
<div style="text-align: center;">1.1, 1.2, and 1.3</div>
  
 
||
 
||
Line 24: Line 29:
  
  
* Matrices, vectors
+
* Vectors and Matrices  
 
* Gauss-Jordan elimination
 
* Gauss-Jordan elimination
 
* Rank of a matrix
 
* Rank of a matrix
Line 40: Line 45:
 
||
 
||
  
<div style="text-align: center;">1.3, 1.4 and 1.5</div>
+
<div style="text-align: center;">2.1, 2.2, 2.3, and 2.4</div>
  
 
||
 
||
Line 52: Line 57:
 
* Inverse functions and the identity function
 
* Inverse functions and the identity function
 
* Vectors and the Inner product
 
* Vectors and the Inner product
 
  
 
||
 
||
  
*
 
 
* Linear transformations and their properties
 
* Linear transformations and their properties
 
* Geometry of Linear Transformations (rotations, scalings and projections)
 
* Geometry of Linear Transformations (rotations, scalings and projections)
Line 70: Line 73:
 
||
 
||
  
<div style="text-align: center;">2.4</div>
+
<div style="text-align: center;">3.1, 3.2, and 3.3</div>
  
 
||
 
||
Line 84: Line 87:
 
||
 
||
  
Image and Kernel of a linear transformation
+
* Image and Kernel of a linear transformation
Span of a vector set
+
* Span of a vector set
Subspace of R<sup>n</sup>
+
* Subspace of R<sup>n</sup>
Linear independence and basis
+
* Linear independence and basis
Dimension
+
* Dimension
Rank-nullity Theorem
+
* Rank-nullity Theorem
  
 
|-
 
|-
Line 98: Line 101:
 
||
 
||
  
<div style="text-align: center;"> </div>
+
<div style="text-align: center;"> 3.4  </div>
  
 
||
 
||
Line 126: Line 129:
 
||
 
||
  
<div style="text-align: center;"> </div>
+
<div style="text-align: center;"> 5.1, 5.2, 5.3, and 5.4 </div>
  
 
||
 
||
Line 146: Line 149:
 
* Transpose of a Matrix
 
* Transpose of a Matrix
 
* Orthonormal vectors
 
* Orthonormal vectors
* Orthogonal Projection (x = xjj + x?)
+
* Orthogonal Projection  
 
* Orthonormal Bases
 
* Orthonormal Bases
 
* Gram-Schmidt process
 
* Gram-Schmidt process
Line 162: Line 165:
 
||
 
||
  
<div style="text-align: center;"> </div>
+
<div style="text-align: center;">6.1, 6.2, and 6.3 </div>
  
 
||
 
||
Line 192: Line 195:
 
||
 
||
  
<div style="text-align: center;"> </div>
+
<div style="text-align: center;">7.1, 7.2, 7.3, and 8.1 </div>
  
 
||
 
||

Revision as of 19:52, 15 June 2020

A comprehensive list of all undergraduate math courses at UTSA can be found here.

The Wikipedia summary of Linear Algebra and its history.

Topics List

Date Sections Topics Prerequisite Skills Student Learning Outcomes
Week 1/2
1.1, 1.2, and 1.3

Systems of Linear Equations

  • Adding and subtracting equations
  • Solving an equation for a specifed variable
  • Equation for a line


  • Vectors and Matrices
  • Gauss-Jordan elimination
  • Rank of a matrix
  • Matrix addition
  • The product Ax
  • Inner product
  • Linear Combinations


Week 3/4
2.1, 2.2, 2.3, and 2.4


Linear Transformations

  • Basics of functions
  • Inverse functions and the identity function
  • Vectors and the Inner product
  • Linear transformations and their properties
  • Geometry of Linear Transformations (rotations, scalings and projections)
  • Matrix Products
  • The Inverses of a linear transform


Week 5/6
3.1, 3.2, and 3.3

Bases and Linear Independence

  • Linear Combinations
  • Dimension in Rn
  • Image and kernel of a function
  • Image and Kernel of a linear transformation
  • Span of a vector set
  • Subspace of Rn
  • Linear independence and basis
  • Dimension
  • Rank-nullity Theorem
Week 7/8
3.4


Similar Matrices and Coordinates

  • Conics (ellipses in particular)
  • Equivalence Relations
  • Coordinates in a subspace of Rn
  • Similar matrices
  • Diagonal matrices


Week 9/10
5.1, 5.2, 5.3, and 5.4


Orthogonality

  • Parallel and perpendicular lines
  • Absolute value function
  • Basic trigonometric function
  • Properties of inner products
  • Perpendicular vectors
  • Magnitude of vectors
  • Transpose of a Matrix
  • Orthonormal vectors
  • Orthogonal Projection
  • Orthonormal Bases
  • Gram-Schmidt process
  • The Least Squares solution


Week 11/12
6.1, 6.2, and 6.3


Determinants

  • Summation notation
  • Sgn function
  • Properties of Determinants
  • Row operations and determinants
  • Invertibility based on determinant
  • Geometric Interpretation of the Determinant
  • Cramer's rule


Week 13/14
7.1, 7.2, 7.3, and 8.1


Eigenvalues and Eigenvectors

  • Finding real roots of a polynomial
  • Finding the kernel of a function
  • Diagonalization
  • Finding eigenvalues
  • Finding eigenvectors
  • Geometric and algebraic multiplicity
  • Spectral Theorem