What you'll learn
Week 1: Modeling Decisions in Low Uncertainty Settings
Week 2: Risk and Reward: Modeling High Uncertainty Settings
Week 3: Choosing Distributions that Fit Your Data
Week 4: Balancing Risk and Reward Using Simulation
Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how to create quantitative models to reflect complex realities, and how to include in your model elements of risk and uncertainty.
You’ll also learn the methods for creating predictive models for identifying optimal choices; and how those choices change in response to changes in the model’s assumptions. You’ll also learn the basics of the measurement and management of risk. By the end of this course, you’ll be able to build your own models with your own data, so that you can begin making data-informed decisions. You’ll also be prepared for the next course in the Specialization.
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are new to this field
Students willing to put in a couple hours to learn about Modeling Risk and Realities
Advanced students wanting to add another skill to their portfolio
Sergei Savin – Associate Professor of Operations, Information and Decisions – The Wharton School
Senthil Veeraraghavan – Associate Professor of Operations, Information and Decisions – The Wharton School
This course includes
Option for learning at your own pace
Videos and reading material about the course
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks