Computer Science Track

Linear
Algebra

From vectors and matrices to SVD and tensors. Built for CS engineers who need rigorous theory with real implementation insight.

18Chapters
5Modules
3DAnimations
CSFocused

What You Will Learn

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3D Interactive Visuals

Every abstract concept rendered in live Three.js -- watch transformations, eigenvectors, and projections in real time.

Rigorous Theory

Full theorem-proof-example structure. Definitions, lemmas, worked problems, and geometric intuition side by side.

CS Applications

PCA, SVD image compression, graphics pipelines, neural network weight matrices, and PageRank.

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Spectral Thinking

From eigenvalues to the spectral theorem. Understand why diagonalisation matters and how SVD generalises it.

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Worked Examples

Every section has fully solved examples with step-by-step calculations and visual confirmation.

Review and Practice

Three-tier review questions per chapter: conceptual, computational, and applied.

Course Modules

18 chapters organised into five progressive modules

What Awaits You

Matrix Transformations

Watch the plane bend, shear, and rotate as you change matrix entries live.

Eigenvector Geometry

See exactly which vectors stay on their span while the transformation acts.

SVD Decomposition

Step through U, Sigma, V and watch a unit circle morph into an ellipse.

Gram-Schmidt Live

Build an orthonormal basis step by step with animated projections.

Ready to think in matrices?

Start from vectors and build all the way to SVD, tensors, and modern CS applications.