Numerical Linear Algebra

About this course

LU decomposition, Cholesky, QR factorization, iterative methods (Jacobi, Gauss-Seidel), conjugate gradient.

• 20 lessons
• 2 h
• advanced

What you'll learn

• Define numerical linear algebra and its primary problem domains
• Identify common applications of linear algebra in professional practice
• Outline the course roadmap from direct to iterative methods
• Recall key matrix properties such as symmetry, positive definiteness, and sparsity
• Explain the significance of vector and matrix norms in numerical computation
• Interpret the condition number and its impact on solution accuracy

Finishing the course

• 80 knowledge-check questions along the way, so you know the ideas stuck before you move on.
• Watching is free and needs no account. Sign in to save your progress. Pass each lesson's quiz (60%+) to earn the certificate. Each certificate has its own public verification link to share, marked quiz-verified.

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