Linda Nozick is a professor in Cornell’s School of Civil and Environmental Engineering. She served as director of the school for more than a decade. Prior to that role, Nozick was the director of the college’s Systems Engineering Program, which she co-founded. Nozick has been the recipient of several awards including a CAREER award from the National Science Foundation and a Presidential Early Career Award for Scientists and Engineers from President Clinton for “the development of innovative solutions to problems associated with the transportation of hazardous waste.” She is a past U.S. Presidential appointee to the U.S Nuclear Waste Technical Review Board. Nozick has authored over 100 peer-reviewed publications, many focused on transportation, the movement of hazardous materials, and the modeling of critical infrastructure systems. Nozick holds a B.S. in systems analysis and engineering from the George Washington University and a M.S.E and Ph.D. in systems engineering from the University of Pennsylvania.
Course Overview
Once you have a sense of risk for a situation, how can you model that risk using the most common tools of the industry?
In this course, you will assess a given situation, select the appropriate modeling tools, and perform a risk analysis. You will begin by identifying the attributes that make a model strong, providing you with a blueprint for creating user-friendly and reliable models for risk analysis. You will explore the most commonly used risk analysis tools, including simulation, fault trees, event trees, Bayesian networks, and statistical tools. Your examination of simulation tools will have you quantifying risk by creating a Monte Carlo simulation and constructing a Bayesian network. Finally, you will discuss mitigation, diversification, and transfer of risk as well as how to pick the correct combination for a given situation. By the end of this course, you will have the necessary foundation to model risk and apply strategies to set you up for success.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Risk Analysis Foundations
- Risk Evaluation
Key Course Takeaways
- Create a Monte Carlo simulation and apply it to quantify risk
- Construct a Bayesian network
- Outline the steps used to design experiments that quantify risk
- Describe how the concepts of mitigation, diversification, and transfer may benefit a given situation
- Identify ways to combine risk management strategies
How It Works
Course Author
Who Should Enroll
- Risk managers and analysts
- Finance and insurance professionals
- Project managers
- Supply chain managers
- Computer and information security engineers
- Software developers
- Engineers
- Executives
- Professionals across industries interested in understanding risk management
100% Online
cornell's Top Minds
career