1 Linear Algebra and Optimization: An Introduction 2 Linear Transformations and Linear Systems 3 Eigenvectors and Diagonalizable Matrices 4 Optimization Basics: A Machine Learning View 5 Advanced Optimization Solutions 6 Constrained Optimization and Duality 7 Singular Value Decomposition 8 Matrix Factorization 9 The Linear Algebra of Similarity 10 The Linear Algebra of Graphs 11 Optimization in Computational Graphs