Schedule
Asynchronous
Delivery method
Online
NCLab Linear Algebra 5 Certificate: Advanced Linear Algebra: Spectral Theory, Matrix Factorization, and Python Applications (Learn-by-doing, 24/7, Online, Self-Paced, Gamified, Realtime 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 5: Advanced Topics and Applications
This advanced Linear Algebra module explores the Spectral Theorem, Singular Value Decomposition (SVD), and QR factorization with a strong focus on real-world applications such as linear regression and image processing. Learners gain a deep understanding of matrix diagonalization, eigenvalue analysis, least-squares problems, and matrix conditioning. Emphasis is placed on computational techniques using Python’s NumPy and SciPy libraries, including solutions for large and sparse matrices. The course supports both theoretical foundations and practical implementation, making it ideal for students pursuing data science, engineering, or quantitative research fields. This is a self-paced, learn-by-doing course that builds strong analytical thinking.
Topics
- Spectral Theorem, QR Factorization, SVD, Least-Squares, Sparse Matrices
Prerequisites
- The REQUIRED prerequisite for this Course is NCLab's Linear Algebra 4.
Sections
Deliverables
0 Credits
Academic Excellence
Earn necessary number of credit hours for completing this content
Professional Program
Launch of Career
Linear Algebra 5 Completion Certificate.
Outcomes
Upon completion, you'll have skills and knowledge in the following advanced topics: Spectral Theorem, QR Factorization, SVD, Least-Squares, Sparse Matrices
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