NCLab Linear Algebra 2 Certificate: Spaces, Eigenvalues and Orthogonality (Learn-by-doing, 24/7, Online, Self-Paced, Gamified, Real-Time Instructional Support)

0 credit hours

Credits awarded upon completion

Self-Paced

Progress at your own speed

50 hours

Estimated learning time

About the Course

Description

Linear Algebra 2 (NCLab) Spaces, Eigenvalues, and Orthogonality. This is an online, self-paced, learn-by-doing course that builds on foundational concepts to explore deeper structures and techniques used across data science, engineering, and advanced mathematics. Learners work with determinants, linear spaces, bases, and coordinate systems, gaining fluency with the column space, null space, and matrix rank. The course introduces eigenvalues and eigenvectors, which play a critical role in machine learning, stability analysis, and computer vision. Additional focus is placed on normed and inner product spaces, orthogonality, and best approximation methods through orthogonal projections. Learners leave with a deeper understanding of how linear algebra supports optimization, modeling, and high-performance computing.

Topics

Determinants, linear space, basis, coordinates, null space, column space, rank, eigenvalues and eigenvectors, normed spaces, inner product spaces, orthogonality, orthogonal projection, best approximation.

Prerequisites

The REQUIRED prerequisite for this Course is NCLab's Linear Algebra 1.

Sections

Schedule

Asynchronous

Delivery method

Online

$500

Deliverables

0 Credits
Academic Excellence
Earn necessary number of credit hours for completing this content
Professional Program
Launch of Career
Linear Algebra 2 Completion Certificate

Outcomes

Upon completion, you'll have the skills and knowledge on the following topics: Determinants, linear space, basis, coordinates, null space, column space, rank, eigenvalues and eigenvectors, normed spaces, inner product spaces, orthogonality, orthogonal projection, best approximation.