Can machine learning algorithms be blindly applied to financial data? Which methods should be used to form an investment strategy? How does machine learning compare to financial econometrics? Can data be harvested to build profitable investment strategies? This course presents an overview of state-of-the-art techniques for financial applications, including forecasting expected investment returns, risk measures, and optimal portfolio allocations. The emphasis will be on methods that accommodate a large number of variables. We expose students to recent results in the fields of asset pricing, risk management, and portfolio choice with one specific objective: designing better-performing investment strategies.