Math 22: Linear Algebra with Applications

Winter 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. January 6 1.1 Systems of Linear Equations
Day 2 Wed. January 8 1.2 Row Reduction and Echelon Forms
Day 3 Fri., January 10 1.3 1.4 Vector Equations; Matrix Equations
Day 4 Mon. January 13 1.4 -1.5 The Matrix Equation Ax=b and Solution Sets of Linear Equations
Day 5 Wed. January 15 1.7 Linear Independence
Day 6 Fri. January 17 4.1, 4.2 Vector spaces, linear transformation, null space, column space
Day 7 Tues. January 21 (x-hour) 4.2, 1.9 Definition of Linear Transformations, Kernel and Range and the standard matrix
Day 8 Wed. January 22 1.9, 2.1 Reading Injectivity and Surjectivity of T: Rn --> Rm from the matrix and Matrix Operations
Day 9 Fri. January 24 2.2 Inverse of a Matrix
Day 10 Mon. January 27 2.3 Invertible Matrix Theorem
Day 11 Wed. January 29 4.3 Linear independent sets; bases
Thrs. January 30 MIDTERM #1
Day 12 Fri. January 31 2.9 Coordinates, Dimension and rank
Day 13 Mon. February 3 4.4/5.4/4.7 Matrix of a transformation, Change of coordinates matrix
Day 14 Wed. February 5 4.7 Change of coordinates matrix and composition of linear transformations
Day 15 Fri. February 7 3.1, 3.2 Determinant and its Properties of Determinants
Day 16 Mon. February 10 5.1, 5.2 Eigenvalues and Characteristic Equation
Day 17 Wed. February 12 5.2, 5.3 Characteristic Equation, Diagonalization
Day 18 Fri. February 14 5.3, 5.4 Diagonalization and linear transformations
Day 19 Mon. February 17 6.1, 6.2 Inner products and Orthogonality
Day 20 Wed. February 19 6.3 Projections
Thrs. February 20 MIDTERM #2
Day 21 Fri. February 21 6.4 Gram-Schmidt Process and Least Squares
Day 22 Mon. February 24 7.1 Diagonalization of Symmetric Matrices
Day 23 Wed. February. 26 4.9, 5.8 Intro to Markov Chains, Iteration Method for Eigenvalues
Day 24 Fri. February 28 4.9, 5.8 Application: Markov Chains & Google's page rank
Day 25 Mon. March 3 + x-hour 7.4 Application: Singular Value decomposition (SVD)
Day 26 Wed. March 5 7.5 Application: Principal Component Analysis (PCA) & Eigenfaces
Day 27 Fri. March 7 No section in book Application -- JPEG compression algorithm.


Page created and maintained by R. Orellana