Math 22: Linear Algebra with Applications

Spring 2025

Syllabus

The following is a tentative syllabus for the course. This page will be updated irregularly.
On the other hand, the weekly syllabus contained in the Homework Assignments page will always be accurate.

Lecture Date Section in Text Brief Description
Day 1 Mon. March 31 1.1 Systems of Linear Equations
Day 2 Wed. April 2 1.2 Row Reduction and Echelon Forms
Day 3 Fri. April 4 1.3 1.4 Vector Equations; Matrix Equations
Day 4 Mon. April 7 1.4 -1.5 The Matrix Equation Ax=b and Solution Sets of Linear Equations
Day 5 Wed. April 9 1.7 Linear Independence
Day 6 Fri. April 11 4.1, 4.2 Vector spaces, linear transformation, null space, column space
Day 7 Mon. April 14 4.2, 1.9 Definition of Linear Transformations, Kernel and Range and the standard matrix
Day 8 Wed. April 16 1.9, 2.1 Reading Injectivity and Surjectivity of T: Rn --> Rm from the matrix and Matrix Operations
Day 9 Fri. April 18 2.2 Inverse of a Matrix
Day 10 Mon. April 21 2.3 Inverse Matrix Theorem
Day 11 Wed. April 23 4.3 Linear independent sets; bases
Thrs. April 24 MIDTERM #1
Day 12 Fri. April 25 2.9 Coordinates, Dimension and rank
Day 13 Mon. April 28 4.4/5.4/4.7 Matrix of a transformation, Change of coordinates matrix
Day 14 Wed. April 30 4.7 Change of coordinates matrix and composition of linear transformations
Day 15 Fri. May 2 3.1, 3.2 Determinant and its Properties of Determinants
Day 16 Mon. May 5 5.1, 5.2 Eigenvectors and Eigenspaces
Day 17 Wed. May 7 5.2, 5.3 Eigenvalues and Characteristic Equation
Day 18 Fri. May 9 5.3, 5.4 Diagonalization and linear transformations
Day 19 Mon. May 12 6.1, 6.2 Inner products and Orthogonality
Day 20 Wed. May 14 6.3 Projections
Thrs. May 15 MIDTERM #2
Day 21 Fri. May 16 6.4 Gram-Schmidt Process and Least Squares
Day 22 Mon. May 19 7.1 Diagonalization of Symmetric Matrices
Day 23 Wed. May 21 4.9, 5.8 Intro to Markov Chains, Iteration Method for Eigenvalues
Day 24 Fri. May 23 4.9, 5.8 Application: Markov Chains & Google's page rank
Day 25 Tues. May 27 (x-hour) 7.4 Application: Singular Value decomposition (SVD)
Day 26 Wed. May 28 7.4 Application of SVD to storing images
Day 27 Fri. May 30 No section in book Application -- JPEG compression algorithm
Day 28 Mon. June 2 Section 7.5 Application: Principal Component Analysis (PCA) & Eigenfaces


Page created and maintained by R. Orellana