This course offers an introduction to optimization methods with applications in data science. A basic understanding of Calculus and Linear Algebra are assumed. We will introduce the theoretical foundation and the fundamental algorithms for optimization and advanced optimization methods for practical problems arising in data science and machine learning applications. Course content includes convex analysis, Lagrangian duality theory, linear and nonlinear programming, conic programming, etc.