Math 22: Linear Algebra with Applications

Spring 2023

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


Page created and maintained by R. Orellana