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.

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## About this Course

### 학습자 경력 결과

## 34%

## 35%

## 10%

### 귀하가 습득할 기술

### 학습자 경력 결과

## 34%

## 35%

## 10%

#### 공유 가능한 수료증

#### 100% 온라인

#### 유동적 마감일

#### 완료하는 데 약 10시간 필요

#### 영어

## 강의 계획 - 이 강좌에서 배울 내용

**완료하는 데 2시간 필요**

## 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.

**완료하는 데 2시간 필요**

**7개의 동영상**

**1개의 읽기 자료**

**1개 연습문제**

**완료하는 데 2시간 필요**

## 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.

**완료하는 데 2시간 필요**

**6개의 동영상**

**1개의 읽기 자료**

**1개 연습문제**

**완료하는 데 2시간 필요**

## 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.

**완료하는 데 2시간 필요**

**12개의 동영상**

**1개의 읽기 자료**

**1개 연습문제**

**완료하는 데 2시간 필요**

## 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.

**완료하는 데 2시간 필요**

**8개의 동영상**

**1개의 읽기 자료**

**1개 연습문제**

### 검토

#### 4.6

##### FUNDAMENTALS OF QUANTITATIVE MODELING의 최상위 리뷰

Very clear and articulate explanation of the concepts. He doesn't skip a step in the sequencing ideas, drawing comparisons and differences, and illustrating both visually and story-telling. Excellent.

Very nice course for beginner, the mathematic level is not high (around french baccalaureat) so available to everyone. I enjoyed a lot this course that show how simple math can be used in real life.

The Course was easy to understand and pretty demonstrative as well. Although if the mathematics behind the equations derived were squeezed into the course briefly, it would have been of great value.

The material is very helpful to get you up to speed quickly. If there could be more emphasis on walking one through the calculations and giving more examples, the course would be a perfect 5 stars.

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.

Course is having ultimate content regarding the understanding of Quantitative modeling and its applications. Having great explanation with examples of linear, power, exponential and log functions.

A great introductory course to quantitative modelling. Videos are very concise and clear with great examples. Course is well balanced between theory and applications. Overall a great experience.

Very good background to quantitative modelling. It gets a bit heavy on the mathematical formulas in places, but if you follow through, it helps cement understanding. Good speed/pace of material.

This is a good course for all of them who wish to work in this field and are unable to do so because of lack of core knowledge. The course helps to build this fundamental conceptual knowledge.

Just finished the course.Well designed and explained.The explanation of some equation could make it more understandable. I would have given it 5star if there was some exercise for practice.

This course helped me to understand, the main concepts about modeling with log, linear power and exponentials functions with very interesting examples of the real life, highly recommended.

I am exactly looking for this course since 7-8 months recently i come across and immedietly registered .\n\nI am going through the concepts covered here. Nice and elaborative. Thank you Dr

### 제공자:

#### 펜실베이니아 대학교

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.

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