Predictive Analytics for Business – with Case Studies
Predictive Analytics for Business – with Case Studies, available at $34.99, has an average rating of 4.35, with 19 lectures, based on 92 reviews, and has 404 subscribers.
You will learn about Learn Predictive Analytics for Business Learn the various applications of Predictive Analytics in business Apply Predictive Analytics in business through the following cases studies: B2B Churn, Customer Segmentation, Direct Marketing, Market Basket Analysis This course is ideal for individuals who are Business Professionals or Business Analysts or Others who are interested in Predictive Analytics It is particularly useful for Business Professionals or Business Analysts or Others who are interested in Predictive Analytics.
Enroll now: Predictive Analytics for Business – with Case Studies
Summary
Title: Predictive Analytics for Business – with Case Studies
Price: $34.99
Average Rating: 4.35
Number of Lectures: 19
Number of Published Lectures: 19
Number of Curriculum Items: 19
Number of Published Curriculum Objects: 19
Original Price: $24.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn Predictive Analytics for Business
- Learn the various applications of Predictive Analytics in business
- Apply Predictive Analytics in business through the following cases studies: B2B Churn, Customer Segmentation, Direct Marketing, Market Basket Analysis
Who Should Attend
- Business Professionals
- Business Analysts
- Others who are interested in Predictive Analytics
Target Audiences
- Business Professionals
- Business Analysts
- Others who are interested in Predictive Analytics
This is an introductory course designed to help business professionals and others learn predictive analytic skills that can be applied in a business setting. Since it is designed for business professionals it doesn’t delve too deeply into the mathematics of the statistical models. We do the following case studies on Rapidminer software: B2B Churn of an office supply distributor, Market Basket Analysis of a retail computer store, Customer Segmentation of a customer database and Direct Marketing. The following models are used: Linear Regression, Logistic Regression, Association Rules, K-means Clustering and Decision Trees. Through these practical case studies we generate actionable business insights!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Common Business Applications of Predictive Analytics
Lecture 3: The Process – CRISP-DM Model
Lecture 4: Data Types, Sources and Structure
Chapter 2: Modeling Methods – Supervised
Lecture 1: Modeling Methods – Prediction – Linear Regression
Lecture 2: Case Study – Excel – Linear Regression
Lecture 3: Modeling Methods – Classification – Logistic Regression
Lecture 4: B2B Churn Case Study – Background and Dataset
Lecture 5: Introduction to Rapidminer Software
Lecture 6: Case Study – Rapidminer – B2B Churn
Lecture 7: Modeling Methods – Classification – Decision Trees
Lecture 8: Direct Marketing Case Study – Background and Dataset
Lecture 9: Case Study – Rapidminer – Direct Marketing
Chapter 3: Modeling Methods – Unsupervised
Lecture 1: Modeling Methods – Unsupervised – Clustering
Lecture 2: Customer Segmentation Case Study – Background and Dataset
Lecture 3: Case Study – Rapidminer – Customer Segmentation
Lecture 4: Modeling Methods – Unsupervised – Association Rules
Lecture 5: Market Basket Case Study – Background and Dataset
Lecture 6: Case Study – Rapidminer – Market Basket Analysis
Instructors
-
John Phillips
CFO Analytics Training, LLC
Rating Distribution
- 1 stars: 4 votes
- 2 stars: 3 votes
- 3 stars: 21 votes
- 4 stars: 35 votes
- 5 stars: 29 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
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