This course covers a wide range of topics in linear algebra, including Gauss Jordan elimination, multiplying matrices, vectors, subspaces, determinants, eigenvalues, and eigenvectors. By the end of the course, students will be able to solve systems of linear equations, understand linear transformations, and work with different types of matrices. The teaching method involves a series of lectures and practical examples to reinforce learning. This course is intended for individuals interested in gaining a solid foundation in linear algebra concepts and applications.
Overview
Syllabus
Prelinear Algebra.
Linear Algebra.
Linear Algebra 2 : Gauss Jordan Elimination.
Linear Algebra 3 : Finding Number of Solutions.
Linear Algebra 4 : Multiplying Matrices.
Linear Algebra 5 : Elimination Matrix & Vectors.
Linear Algebra 6 : Vectors & Spans.
Linear Algebra 7 : Subspaces.
Linear Algebra 8 : Basis & Cauchy Schwarz Inequality.
Linear Algebra 9 : Plane Equations & Vector Triangle Inequality.
Linear Algebra 10 : Cross Product.
Linear Algebra 11: Null Space.
Linear Algebra 12 : Solving Ax = b.
Linear Algebra 13 : Linear Transformations.
Linear Algebra 14 : Magic Transformations.
Linear Algebra 15 : Rotate & Scale Vectors.
Linear Algebra 16 : Linear Transformation Projections.
Linear Algebra 17 : Determinants.
Linear Algebra 18 : Determinants & Systems of Equations.
Linear Algebra 19 : Find Area with Determinants.
Linear Algebra 20 : Transpose.
Linear Algebra 21 : 4 Fundamental Subspaces.
Linear Algebra 22 : Orthogonal Complements.
Linear Algebra 23 : Projections on Any Subspace.
Linear Algebra 24 : Least Squares Method.
Linear Algebra 25 : Change of Basis Matrix.
Linear Algebra 26 : Orthonormal Basis.
Linear Algebra 27 : Gram-Schmidt Process.
Linear Algebra 28 : Eigenvalues and Eigenvectors.
Linear Algebra 29 : Final Video.
Taught by
Derek Banas
