Emory University
Marketing Analytics Capstone Project

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Emory University

Marketing Analytics Capstone Project

David Schweidel

Instructor: David Schweidel

3,318 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.5

(29 reviews)

11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.5

(29 reviews)

11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

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Assessments

4 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Foundations of Marketing Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 6 modules in this course

This module will define the goals and activities for the marketing analytics capstone project.

What's included

2 readings1 discussion prompt

In this module, we will begin to examine individual variables and their relationship to the status of the loan. Note, this module includes review items from previous courses in the specialization. This content is not required, but recommended as content to revisit.

What's included

9 videos2 readings1 peer review1 discussion prompt

While there are many ways to build a classification model, we will focus on using logistic regression, a common tool for marketing problems in which the dependent variable is binary. We will begin by choosing a single predictor variable and then determine which other variables need to be added to our analysis. In this module, we will focus on developing alternative models that all have a single predictor.

What's included

3 readings1 assignment2 discussion prompts

In the previous module, we estimated a model linking home ownership to whether or not a loan is considered risky. In this module, we will begin by assessing the accuracy of this model relative to a naïve model. We will then use this spreadsheet as a means of assessing how well the model performs when different predictors are used.

What's included

1 reading1 assignment1 peer review

In this module, we will generalize the logistic regression tool that was developed to include multiple predictor variables. We will also consider an alternative means of evaluating the performance of the model.

What's included

2 readings2 assignments1 peer review2 discussion prompts

This module provides a final congratulatory video from Professor David Schweidel.

What's included

1 video

Instructor

David Schweidel
Emory University
11 Courses64,891 learners

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Recommended if you're interested in Marketing

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4.5

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Reviewed on Apr 23, 2020

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