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.
Este curso forma parte de Programa Especializado - Business and Financial Modeling
Modeling Risk and Realities
ofrecido por
Acerca de este Curso
Resultados profesionales del estudiante
44%
32%
Habilidades que obtendrás
Resultados profesionales del estudiante
44%
32%
Certificado para compartir
100 % en línea
Curso 3 de 5 en
Fechas límite flexibles
Aprox. 9 horas para completar
Inglés (English)
Programa - Qué aprenderás en este curso
Week 1: Modeling Decisions in Low Uncertainty Settings
This module is designed to teach you how to analyze settings with low levels of uncertainty, and how to identify the best decisions in these settings. You'll explore the optimization toolkit, learn how to build an algebraic model using an advertising example, convert the algebraic model to a spreadsheet model, work with Solver to discover the best possible decision, and examine an example that introduces a simple representation of risk to the model. By the end of this module, you'll be able to build an optimization model, use Solver to uncover the optimal decision based on your data, and begin to adjust your model to account for simple elements of risk. These skills will give you the power to deal with large models as long as the actual uncertainty in the input values is not too high.
Week 2: Risk and Reward: Modeling High Uncertainty Settings
What if uncertainty is the key feature of the setting you are trying to model? In this module, you'll learn how to create models for situations with a large number of variables. You'll examine high uncertainty settings, probability distributions, and risk, common scenarios for multiple random variables, how to incorporate risk reduction, how to calculate and interpret correlation values, and how to use scenarios for optimization, including sensitivity analysis and the efficient frontier. By the end of this module, you'll be able to identify and use common models of future uncertainty to build scenarios that help you optimize your business decisions when you have multiple variables and a higher degree of risk.
Week 3: Choosing Distributions that Fit Your Data
When making business decisions, we often look to the past to make predictions for the future. In this module, you'll examine commonly used distributions of random variables to model the future and make predictions. You'll learn how to create meaningful data visualizations in Excel, how to choose the the right distribution for your data, explore the differences between discrete distributions and continuous distributions, and test your choice of model and your hypothesis for goodness of fit. By the end of this module, you'll be able to represent your data using graphs, choose the best distribution model for your data, and test your model and your hypothesis to see if they are the best fit for your data.
Week 4: Balancing Risk and Reward Using Simulation
This module is designed to help you use simulations to enabling compare different alternatives when continuous distributions are used to describe uncertainty. Through an in-depth examination of the simulation toolkit, you'll learn how to make decisions in high uncertainty settings where random inputs are described by continuous probability distributions. You'll also learn how to run a simulation model, analyze simulation output, and compare alternative decisions to decide on the most optimal solution. By the end of this module, you'll be able to make decisions and manage risk using simulation, and more broadly, to make successful business decisions in an increasing complex and rapidly evolving business world.
Revisiones
Principales revisiones sobre MODELING RISK AND REALITIES
covers good amount of material and exactly what is in the outline, presented with enough detail to follow. Good walk-through of the spreadsheets helps understanding, easy to follow along and practice.
Material was very well presented. Week 3 was challenging, but taking time to print out the slides, work through them rigorously proved very helpful. I found all sections very, very informative.
Tough course but challenging in a good way. This course challenges you to think differently and will improve your skillset in many areas including analysis, critical thinking, and numbers.
Awesome couse for learning applications of statistics in real world problems. They show how can we optimize the results using the most common tool among all business environments: excel.
one of the best, as a data analyst this course will give you the necessary knowledge needed in business intelligence and financial modelling. The last week was very challenging but apt.
This course is very informative and maintains a good pace for the learner. Although it might not be challenging enough. I still recommend it to anyone wanting to learn this material.
Really great course! Learnt a lot, more than promised by the course description. The course instructors are really good and very articulate. Thoroughly pleased with the course!
Great examples, the best course of the specialization so far.\n\nWeek 3 was a little bit slow. I think it was going through some theory that was already covered by course 1.
I thoroughly enjoyed this course. I not only learned a lot in terms of ability to use Excel and am now better equipped to approach data in certain (and uncertain) situations
4 starts only because Week 3 lecturer is not good at all. hard to follow, leaves things on slides unexplained. throws bunch of formulas forever without showing it in excel.
Not too bad of a course. Fairly beginner but there is some interesting things to learn. I would recommend watching the videos at 1.5x speed because they speak fairly slow.
The professors are amazing. I could grasp all the concepts easily because of the good pace maintained by the professors. Thank you so much for this course!
Good course, explanations sometime a bit hard to follow, but came away with a pretty solid understanding of how to run constraint optimizations in Excel.
Overall very interesting, though the teachers waffle a bit at times and question 4 in the final test is not of an acceptable standard for a fixed course.
Professor Senthil ruined Week 3 with no explanation and reading exactly the same story from the slides. Rest course is interesting and engaging. Thanks.
The course was what I expected it to be. I was desperately looking for enlightenment in model risk and realities which was well delivered in the course.
It's hard to understand an accent and learn a brand new material at the same time. Having subtitles was very much helpful. Great course overall, thanks!
A well-structured and practice-oriented course with a few useful practical tips about Excel-based business models focusing on risk and reward aspects.
Excellent course. Great and useful examples given by instructors. Also, very helpful that editables files used in examples are available for students.
Good information on the use of spreadsheets. I had difficulty in Modules 3 & 4 on spreadsheet usage. Could tie instruction closer to quiz questions.
Acerca de Universidad de Pensilvania
Acerca de Programa especializado Business and Financial Modeling
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
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¿Qué recibiré si me suscribo a este Programa especializado?
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