2. Matrices

• Matrix algebra (addition, multiplication, inverse)
• Determinants
• Solving systems of linear equations
• Transformations in geometry using matrices
• Eigenvalues and eigenvectors (introduced lightly)



Usefulness: Fundamental in computer graphics, quantum mechanics, and data science.