Linear Algebra

Vectors, matrices and transformations — the math that runs machine learning, graphics and scientific computing.

intermediate~35 hours11 topics~21h of lessonsRoadmap Level 2

CS proofs, algorithms and ML are all math under the hood; the notation pays off everywhere.

Learning Path
07 stages
11 topics · 7 stages0/11 completed
01

Fundamentals

Start from zero. Build the vocabulary.

Vectors and Vector Spaces~60 minbeginnerMatrices and Operations~75 minbeginner
02

Core Concepts

The ideas you cannot skip.

Linear Transformations~75 minintermediateSolving Linear Systems: Gaussian Elimination~90 minintermediateDeterminants and Matrix Inverses~75 minintermediate
03

Intermediate

Connect ideas and go deeper.

Eigenvalues and Eigenvectors~90 minadvancedDiagonalization and SVD~90 minadvanced
04

Advanced

Beyond the basics.

Bases, Dimension and Orthogonality~90 minadvanced
05

Practice

Solve problems until it sticks.

Practice Set: Linear Algebra~180 minintermediate
06

Projects

Apply everything in real work.

Project: 3D Transformations Engine~360 minadvanced
07

Interview Prep

Convert knowledge into offers.

Linear Algebra for ML Interviews~60 minadvanced