Math 22: Linear Algebra with Applications

Spring 2021

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


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