The objective of the course is to examine the construction of computational algorithms in solving financial problems, such as risk-aware decision-making, asset pricing, portfolio optimization, and hedging. Considerable attention is devoted to the application of computational and programming techniques to financial, investment and risk management problems. Materials in this course are quantitative and computational in nature as well as analytical. Topics include mean-variance portfolio optimization, simulation (Monte Carlo) methods, scenario-based risk optimization, hedging, uncertainty modeling, asset pricing, simulating stochastic processes, and numerical solutions of differential equations. Python is the primary computational and modeling software used in this course, we also briefly describe other programming environments such as R, Matlab and C/C++ used in financial engineering. Practical aspects of financial and risk modeling, which are used by industry practitioners, are emphasized.