CSE1003

Linear Algebra for Computing

Core Courses

A foundational course in linear algebra tailored for computing applications, covering vectors, matrices, linear systems, eigenvalues, singular value decomposition, and linear transformations. Students gain both theoretical understanding and practical computational skills essential for data science, graphics, and machine learning.

12 Chapters

Chapters

Ch 1FREE

Fundamentals of Vectors and Linear Operations

9 min
Ch 2FREE

Solving Linear Systems and Matrix Methods

12 min
Ch 3

Vector Spaces, Subspaces, and Linear Independence

14 min

Unlock all chapters — plans from $6/mo

Ch 4

Orthogonality and Projections

10 min

Unlock all chapters — plans from $6/mo

Ch 5

Understanding Determinants and Their Applications

10 min

Unlock all chapters — plans from $6/mo

Ch 6

Finding and Using Eigenvalues and Eigenvectors

10 min

Unlock all chapters — plans from $6/mo

Ch 7

The Singular Value Decomposition

8 min

Unlock all chapters — plans from $6/mo

Ch 8

Understanding Linear Transformations and Matrix Representation

15 min

Unlock all chapters — plans from $6/mo

Ch 9

Introduction to Complex Vectors and Matrices

8 min

Unlock all chapters — plans from $6/mo

Ch 10

Real-World Applications of Linear Algebra

9 min

Unlock all chapters — plans from $6/mo

Ch 11

Computational Methods for Linear Systems

12 min

Unlock all chapters — plans from $6/mo

Ch 12

Probability Statistics and Linear Algebra

12 min

Unlock all chapters — plans from $6/mo