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Coursera, Richard Waterman – Fundamentals of Quantitative Modeling

(8 customer reviews)

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Short Description:
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.

Description

Fundamentals of Quantitative Modeling

By Richard Waterman, University of Pennsylvania

About this Course

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.

Fundamentals of Quantitative Modeling is course 1 of 5 in the Business and Financial Modeling Specialization.

Wharton’s Business and Financial Modeling Specialization is designed to help you make informed business and financial decisions. These foundational courses will introduce you to spreadsheet models, modeling techniques, and common applications for investment analysis, company valuation, forecasting, and more. When you complete the Specialization, you’ll be ready to use your own data to describe realities, build scenarios, and predict performanc

Syllabus

Week 1

  • Module 1: Introduction to Models

Week 2

  • Module 2: Linear Models and Optimization

Week 3

  • Module 3: Probabilistic Models

Week 4

  • Module 4: Regression Models

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