This capstone project will give you an opportunity to apply what we have covered in the Foundations of Marketing Analytics specialization. By the end of this capstone project, you will have conducted exploratory data analysis, examined pairwise relationships among different variables, and developed and tested a predictive model to solve a marketing analytics problem. It is highly recommended that you complete all courses within the Foundations of Marketing Analytics specialization before starting the capstone course.
이 강좌는 Foundations of Marketing Analytics 전문 분야의 일부입니다.
Marketing Analytics Capstone Project
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 전문 분야의 6개 강좌 중 6번째 강좌:
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완료하는 데 약 12시간 필요
권장: 3 hours/week
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자막: 영어
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Emory University, located in Atlanta, Georgia, is one of the world's leading research universities. Its mission is to create, preserve, teach and apply knowledge in the service of humanity.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 1시간 필요
Marketing Analytics Project Description
This module will define the goals and activities for the marketing analytics capstone project.
완료하는 데 1시간 필요
2 readings
2개의 읽기 자료
Capstone Overview15m
Pre-Readings30m
완료하는 데 4시간 필요
Exploratory Analysis
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.
완료하는 데 4시간 필요
9개 동영상 (총 91분), 2 readings, 1 quiz
9개의 동영상
Meaningful Marketing Insights - Course Goals & Example 2: Performing Arts Centers8m
Meaningful Marketing Insights - Organizing Data10m
Meaningful Marketing Insights - The Motion Picture Industry12m
Meaningful Markting Insights - Excel Analysis of Motion Picture Industry Data13m
Meaningful Marketing Insights - Displaying Conditional Distributions4m
Meaningful Marketing Insights - Analyzing Qualitative Variables3m
Meaningful Marketing Insights - Steps in Constructing Histograms11m
Meaningful Marketing Insights - Common Descriptive Statistics for Quantitative Data14m
2개의 읽기 자료
Activity & Explanation of Review Content45m
Meaningful Marketing Insights - Parts 2 - 340m
완료하는 데 2시간 필요
Data Preparation and Model Building
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.
완료하는 데 2시간 필요
3 readings
3개의 읽기 자료
Data Preparation Instructions20m
Populating the Template20m
Review Forecasting Models for Marketing Decisions, Parts 1 - 310m
1개 연습문제
Logistic Regression Practice6m
완료하는 데 1시간 필요
Model Validation and Comparison
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.
완료하는 데 1시간 필요
1 reading
1개의 읽기 자료
Model Validation20m
1개 연습문제
Model Validation5m
Foundations of Marketing Analytics 전문 분야 정보
In this specialization you will learn how to:
• Find, extract, organize and describe data to support business decisions
• Identify, quantify and interpret relationships between variables
• Derive customer insights from your data
• Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions
• Present and justify a course of action to management
The capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.
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