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Syllabus→Demo

18 topics, 24 prerequisite links. The keystones — Linear Systems and Gaussian Elimination (14), Four Fundamental Subspaces (11), Matrix Algebra and Inverses (8) — have the most topics resting on them.

Not practisedStrugglingLearningMastered· ✓ = you marked it done
All topics in learning order
  1. ✓ Linear Systems and Gaussian Elimination — starting point
  2. Matrix Algebra and Inverses — needs Linear Systems and Gaussian Elimination
  3. ✓ Vector Subspaces — starting point
  4. Four Fundamental Subspaces — needs Linear Systems and Gaussian Elimination
  5. ✓ Linear Independence and Span — needs Vector Subspaces
  6. Basis and Dimension — needs Linear Independence and Span, Four Fundamental Subspaces
  7. Linear Transformations and Matrix Representations — needs Basis and Dimension, Matrix Algebra and Inverses
  8. Inner Products and Norms — starting point
  9. Orthogonal Subspaces and Complements — needs Inner Products and Norms, Four Fundamental Subspaces
  10. Projections and Least Squares — needs Orthogonal Subspaces and Complements
  11. Gram-Schmidt and QR Factorization — needs Inner Products and Norms, Projections and Least Squares
  12. Determinants and Properties — needs Matrix Algebra and Inverses
  13. Eigenvalues and Eigenvectors — needs Determinants and Properties, Four Fundamental Subspaces
  14. Matrix Diagonalization — needs Eigenvalues and Eigenvectors, Basis and Dimension
  15. Symmetric Matrices and Spectral Theorem — needs Matrix Diagonalization, Gram-Schmidt and QR Factorization
  16. Positive Definite Matrices — needs Symmetric Matrices and Spectral Theorem
  17. Singular Value Decomposition (SVD) — needs Symmetric Matrices and Spectral Theorem, Projections and Least Squares
  18. Engineering Applications — needs Singular Value Decomposition (SVD), Projections and Least Squares