Course Content
Week 1: Introduction to linear algebra, vectors and geometry
Week 2: Matrices and matrix operations
Week 3: Systems of linear equations
Week 4: Solution methods (Gaussian elimination)
Week 5: Determinants
Week 6: Matrix inverse and applications
Week 7: Vector spaces and subspaces
Week 8: Basis and dimension
Week 9: Linear transformations
Week 10: Eigenvalues and eigenvectors
Week 11: Diagonalization
Week 12: Applications in IT (ML, graphics, PCA) & review
Learning Outcomes
Upon successful completion of the course, students will be able to:
Understand fundamental concepts of linear algebra (vectors, matrices, spaces)
Solve systems of linear equations using analytical and computational methods
Perform matrix operations and understand their properties
Compute determinants and matrix inverses
Analyze vector spaces and subspaces
Compute eigenvalues and eigenvectors
Apply linear algebra in IT domains (machine learning, graphics, data science)
Use software tools for linear algebra computations
Develop mathematical reasoning and problem-solving skills
