Courses

​​Whether you're a product developer faced with complex design choices, a financial analyst tasked to predict market volatility, or a general manager expanding business to a new market, decisions are often made under uncertainty. This introductory course will teach students how to approach and model complex decisions. In the context of both business and engineering, students will learn innovative frameworks and applications to make better “bets.”

We will explore theoretical frameworks centered on framing decisions and making trade-offs. Students will learn the difference between decision analysis based on experience (a posteriori) and analysis independent of experience (a priori). We will look at new research on intuition in decision-making and framing ambiguous problems without clear, singular outcomes. We’ll also examine new methods inspired by animal behavior, such as swarm intelligence, which derives wisdom from crowds.

Next, we will focus on applying these frameworks using basic simulation and modeling. We’ll cover common techniques and tools that can be applied across a broad spectrum of domains (operations, finance, marketing, and product development). Assignments and case studies will include sensitivity analysis and Monte Carlo simulation, frequently used by Wall Street and business analysts to make predictions. We will also discuss forward-looking AI applications for more complex decisions. Students will come away with the ability to appropriately frame different types of complex problems and apply new decision frameworks and applications to their own domain.