How can you put data to work for you? Specifically, how can numbers in a spreadsheet tell us about present and past business activities, and how can we use them to forecast the future? The answer is in building quantitative models, and this course is designed to help you understand the fundamentals of this critical, foundational, business skill. Through a series of short lectures, demonstrations, and assignments, you’ll learn the key ideas and process of quantitative modeling so that you can begin to create your own models for your own business or enterprise. By the end of this course, you will have seen a variety of practical commonly used quantitative models as well as the building blocks that will allow you to start structuring your own models. These building blocks will be put to use in the other courses in this Specialization.
Offert par


À propos de ce cours
Compétences que vous acquerrez
- Modeling
- Linear Regression
- Probabilistic Models
- Regression Analysis
Offert par

Université de Pennsylvanie
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
Programme de cours : ce que vous apprendrez dans ce cours
Module 1: Introduction to Models
In this module, you will learn how to define a model, and how models are commonly used. You’ll examine the central steps in the modeling process, the four key mathematical functions used in models, and the essential vocabulary used to describe models. By the end of this module, you’ll be able to identify the four most common types of models, and how and when they should be used. You’ll also be able to define and correctly use the key terms of modeling, giving you not only a foundation for further study, but also the ability to ask questions and participate in conversations about quantitative models.
Module 2: Linear Models and Optimization
This module introduces linear models, the building block for almost all modeling. Through close examination of the common uses together with examples of linear models, you’ll learn how to apply linear models, including cost functions and production functions to your business. The module also includes a presentation of growth and decay processes in discrete time, growth and decay in continuous time, together with their associated present and future value calculations. Classical optimization techniques are discussed. By the end of this module, you’ll be able to identify and understand the key structure of linear models, and suggest when and how to use them to improve outcomes for your business. You’ll also be able to perform present value calculations that are foundational to valuation metrics. In addition, you will understand how you can leverage models for your business, through the use of optimization to really fine tune and optimize your business functions.
Module 3: Probabilistic Models
This module explains probabilistic models, which are ways of capturing risk in process. You’ll need to use probabilistic models when you don’t know all of your inputs. You’ll examine how probabilistic models incorporate uncertainty, and how that uncertainty continues through to the outputs of the model. You’ll also discover how propagating uncertainty allows you to determine a range of values for forecasting. You’ll learn the most-widely used models for risk, including regression models, tree-based models, Monte Carlo simulations, and Markov chains, as well as the building blocks of these probabilistic models, such as random variables, probability distributions, Bernoulli random variables, binomial random variables, the empirical rule, and perhaps the most important of all of the statistical distributions, the normal distribution, characterized by mean and standard deviation. By the end of this module, you’ll be able to define a probabilistic model, identify and understand the most commonly used probabilistic models, know the components of those models, and determine the most useful probabilistic models for capturing and exploring risk in your own business.
Module 4: Regression Models
This module explores regression models, which allow you to start with data and discover an underlying process. Regression models are the key tools in predictive analytics, and are also used when you have to incorporate uncertainty explicitly in the underlying data. You’ll learn more about what regression models are, what they can and cannot do, and the questions regression models can answer. You’ll examine correlation and linear association, methodology to fit the best line to the data, interpretation of regression coefficients, multiple regression, and logistic regression. You’ll also see how logistic regression will allow you to estimate probabilities of success. By the end of this module, you’ll be able to identify regression models and their key components, understand when they are used, and be able to interpret them so that you can discuss your model and convince others that your model makes sense, with the ultimate goal of implementation.
Avis
- 5 stars71,94 %
- 4 stars22,26 %
- 3 stars4,55 %
- 2 stars0,75 %
- 1 star0,47 %
Meilleurs avis pour FUNDAMENTALS OF QUANTITATIVE MODELING
The explanations were lucid and to the point.Much of the emphasis was laid on conceptual clarity rather than solving mechanically the equations. A good course to build intuitive understanding.
This is an excellent overview. In my opinion it is suitable to people who have studied the concepts before (maybe a long time back in college) and need a refresher before diving into details.
Course was very interesting, However I wish there were easier ways to explain to details also the instruction , I would recommend to grab the students attention more to make it more understandable.
excellent course teaches you basics in an easy to learn manner. Lots of good information for someone looking to transition into the world of financial analytics or as a refresher of basic concepts.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Une aide financière est-elle possible ?
D'autres questions ? Visitez le Centre d'Aide pour les Étudiants.