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Linear Algebra Lecture notes 2011 spring semester 
1.1 Vectors and Matrices in Engineering and Mathematics; nSpace 1.2 Dot Product and Orthogonality 
7.1 Basis and Dimension 7.2 Properties of Bases 
1.2 Dot Product and Orthogonality 1.3 Vector Equations of Lines and Planes 2.1 Introduction to Systems of Linear Equations

7.2 Properties of Bases 7.3 The Fundamental Spaces of a Matrix 
2.1 Introduction to Systems of Linear Equations 2.2 Solving Linear System by Row Reduction 
7.3 The Fundamental Spaces of a Matrix 7.4 The Dimension Theorem and Its Implications 
2.2 Solving Linear System by Row Reduction 3.1 Operations on Matrices 
7.5 The Rank Theorem and Its Implications 
3.2 Inverses; Algebraic Properties of Matrices 
7.7 The Projection Theorem and Its Implications 
3.3 Elementary Matrices; A Method for Finding a Inverses

7.9 Orthonormal Bases and the GramSchmidt Process 
3.3 Elementary Matrices; A Method for Finding a Inverse 
7.11 Coordinates with Respect to a Basis 
3.4 Subspaces and Linear Independence 3.5 The Geometry of Linear Systems 
8.1 Matrix Representations of Linear Transformations 
3.5 The Geometry of Linear Systems 3.6 Matrices with Special Forms 
8.2 Similarity and Diagonalizability 
4.1 Determinants; Cofactor Expansions 4.2 Propositions of Determinant 
8.3 Othogonal Diagonalizability; Functions of a Matrix 
4.3 Cramer's Rule; Formula for a Inverse; Applicaitons for Determinants 4.4 A First Look at Eigenvalues and Eigenvectors 
Kinka_LA_14week_A Memorial Day 
4.4 A First Look at Eigenvalues and Eigenvectors 6.1 Matrices as Transformations 
8.4 Quadratic Forms 
6.2 Geometry of Linear Operators 6.3 Kernel and Range 6.4 Composition and Invertibility of Transformations 
8.8 Complex Eigenvalues and Eigenvectors 8.9 Hermitian, Unitary, and Normal Matrices 
9.1 Vector Space Axioms 9.2 Inner Product Spaces; Fourier Series 

+Midterm Exam  +Final Exam 