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Supervised Learning and Its Applications in Marketing
  • Level Foundation
  • المدة 22 ساعات hours
  • الطبع بواسطة O.P. Jindal Global University
  • Offered by

عن

Welcome to the Supervised Learning and Its Applications in Marketing course! Supervised learning is the process of making an algorithm to learn to map an input to a particular output. Supervised learning algorithms can help make predictions for new unseen data. In this course, you will use the Python programming language, which is an effective tool for machine learning applications. You will be introduced to the supervised learning techniques: regression and classification. The course will focus on the applications of these techniques in the domain of marketing. With the growing amount of data and applications of machine learning in marketing, we can easily find examples of the usage of machine learning in marketing efforts. Companies are starting to use machine learning to better understand customer behaviors and identify different customer segments based on their activity patterns. Many organizations also use machine learning to predict future customer behaviors, such as what items they are likely to purchase, which websites they are likely to visit, and who are likely to churn. With endless use cases of machine learning for marketing, companies of all sizes can benefit from using machine learning for their marketing efforts. To succeed in this course, you should have a basic understanding of Python. You will also need certain software requirements, including an Anaconda navigator.

الوحدات

Course Introduction

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1 Videos

  • Course Intro video

1 Readings

  • Course Overview

Major Challenges Marketers Face Today

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1 Assignment

  • Major Challenges Marketers Face Today

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  • Major Challenges Marketers Face Today

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  • Essential Reading: Major Challenges Marketers Face Today

Introduction to Machine Learning for Marketing

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1 Assignment

  • Introduction to Machine Learning for Marketing

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  • Introduction to Machine Learning for Marketing

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  • Essential Reading: Introduction to Machine Learning for Marketing

Concepts for Machine Learning in Marketing

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  • Concepts for Machine Learning in Marketing

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  • Concepts for Machine Learning in Marketing

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  • Essential Reading: Concepts for Machine Learning in Marketing

Introduction to Supervised Learning in Marketing

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  • Introduction to Supervised Learning in Marketing 

1 Discussions

  • Understanding the Applications of Supervised Learning in Marketing

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  • Introduction to Supervised Learning in Marketing 

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  • Essential Reading: Introduction to Supervised Learning in Marketing 

Problem Workflow for Supervised Learning and Its Techniques 

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  • Problem Workflow for Supervised Learning and Its Techniques 

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  • Problem Workflow for Supervised Learning and Its Techniques 

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  • Essential Reading: Problem Workflow for Supervised Learning and Its Techniques 

Key Performance Indicators and Visualizations

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  • Key Performance Indicators and Visualizations

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  • Essential Reading: Key Performance Indicators and Visualizations

Drivers Behind Marketing Engagement 

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  • Drivers Behind Marketing Engagement

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  • Drivers Behind Marketing Engagement

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  • Essential Reading: Drivers Behind Marketing Engagement

Decision Trees 

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  • Decision Trees 

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  • Essential Reading: Decision Trees 

Week 1 Graded Quiz: Supervised Learning in Marketing 

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  • Graded Quiz: Supervised Learning in Marketing 

From Engagement to Conversion 

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  • From Engagement to Conversion 

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  • From Engagement to Conversion 

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  • Essential Reading: From Engagement to Conversion

Interpreting Decision

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  • Interpreting Decision Trees

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  • Essential Reading: Interpreting Decision Trees

Importance of Product Analytics

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  • Importance of Product Analytics

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Product Analytics Using Python 

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  • Product Analytics Using Python 

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  • Product Analytics Using Python 

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  • Essential Reading: Product Analytics Using Python 

Product Recommender System 

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  • Product Recommender System 

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Collaborative Filtering 

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  • Collaborative Filtering 

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Building Product Recommendation Engine Using Python

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  • Building Product Recommendation Engine Using Python

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  • Building Product Recommendation Engine Using Python

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Item-Based Collaborative Filtering and Recommendations

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  • Item-Based Collaborative Filtering and Recommendations

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  • Application of Supervised Learning in Product Recommender System

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  • Item-Based Collaborative Filtering and Recommendations

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  • Essential Reading: Item-Based Collaborative Filtering and Recommendations 

Week 2 Graded Quiz: Deriving Insights from Data and Product Recommender System 

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  • Graded Quiz: Deriving Insights from Data and Product Recommender System 

Understanding Customer Behavior 

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  • Understanding Customer Behavior 

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  • Understanding Customer Behavior 

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  • Essential Reading: Understanding Customer Behavior 

Conducting Customer Analytics with Python 

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  • Conducting Customer Analytics with Python 

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  • Conducting Customer Analytics with Python 

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  • Essential Reading: Conducting Customer Analytics with Python

Predictive Analytics in Marketing 

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  • Predictive Analytics in Marketing 

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  • Essential Reading: Predictive Analytics in Marketing 

Predicting the Likelihood of Marketing Engagement Using Python 

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1 Assignment

  • Predicting the Likelihood of Marketing Engagement Using Python 

1 Discussions

  • Supervised Learning to Personalize Marketing and Build Strategies

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  • Predicting the Likelihood of Marketing Engagement Using Python 

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  • Essential Reading: Predicting the Likelihood of Marketing Engagement Using Python

Customer Lifetime Value 

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  • Essential Reading: Customer Lifetime Value

Evaluating Regression Models

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  • Evaluating Regression Models

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  • Evaluating Regression Models

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  • Essential Reading: Evaluating Regression Models

Predicting the Three-Month CLV with Python: Part I

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  • Predicting the Three-Month CLV with Python: Part I

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  • Predicting the Three-Month CLV with Python: Part I

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  • Essential Reading: Predicting the Three-Month CLV with Python: Part I 

Predicting the Three-Month CLV with Python: Part II  

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  • Predicting the Three-Month CLV with Python: Part II 

1 Discussions

  • Customer Churn Prediction Using Supervised Learning

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  • Predicting the Three-Month CLV with Python: Part II 

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  • Essential Reading: Predicting the Three-Month CLV with Python: Part II

Week 3 Graded Quiz: Personalized Marketing and Customer Lifetime Value

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  • Graded Quiz: Personalized Marketing and Customer Lifetime Value

Customer Retention 

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  • Customer Retention 

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  • Customer Retention 

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  • Essential Reading: Customer Retention

Artificial Neural Networks (ANNs)

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  • Artificial Neural Networks (ANNs)

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  • Artificial Neural Networks (ANNs)

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  • Essential Reading: Artificial Neural Networks (ANNs)

Predicting Customer Churn with Python: Part I 

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  • Predicting Customer Churn with Python: Part I

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  • Predicting Customer Churn with Python: Part I

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  • Essential Reading: Predicting Customer Churn with Python: Part I

Predicting Customer Churn with Python: Part II 

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  • Predicting Customer Churn with Python: Part II 

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  • Predicting Customer Churn with Python: Part II 

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  • Essential Reading: Predicting Customer Churn with Python: Part II

Real-Life Challenges in Applying Supervised Learning Models 

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  • Real-Life Challenges in Applying Supervised Learning Models 

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  • Real-Life Challenges in Applying Supervised Learning Models 

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  • Essential Reading: Real-Life Challenges in Applying Supervised Learning Models 

Standardized Framework for Success 

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  • Standardized Framework for Success 

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  • Standardized Framework for Success 

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  • Essential Reading: Standardized Framework for Success 

Industry Views on AI strategy

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  • Industry Views on AI strategy

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  • Industry Views on AI strategy

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  • Essential Reading: Industry Views on AI strategy

Future Scope

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  • Future Scope

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  • Future Scope

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  • Essential Reading: Future Scope

Week 4 Graded Quiz: Retaining customers and Deployment of Supervised Learning Models 

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  • Graded Quiz: Retaining ustomers and Deployment of Supervised Learning Models 

Course Wrap-Up Video

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  • Course Wrap-Up Video

Auto Summary

Embark on a transformative learning journey with the "Supervised Learning and Its Applications in Marketing" course, designed to integrate cutting-edge machine learning techniques into your marketing strategies. This foundational course demystifies supervised learning, focusing on key methodologies like regression and classification, and their real-world applications in the marketing domain. Guided by expert instruction from Coursera, this course leverages the powerful Python programming language to teach you how to develop algorithms that predict customer behaviors, identify distinct customer segments, and foresee future purchasing patterns. By implementing these techniques, you'll gain the ability to optimize marketing efforts and drive business growth. Spanning 1320 minutes, this comprehensive program requires a basic understanding of Python and access to Anaconda navigator software. Available under the Starter subscription, this course is ideal for marketing professionals, data enthusiasts, and anyone eager to harness the potential of machine learning to revolutionize their marketing strategies. Join now and stay ahead in the dynamic field of sales and marketing!

Ambica Ghai
Instructor

Ambica Ghai