Machine Learning for Marketing in Python

Course Cover

5

(3)

compare button icon

Course Features

icon

Duration

4 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Mobile, Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

4 hours

Course Description

The major advancement in machine learning is the rise of machine learning. This almost sounds like the "rise and rise of machines". Statistics have revolutionized marketing. Machine learning can optimize customer journeys to maximize customer satisfaction and lifetime value. This course will give you the foundation tools to improve your company's marketing strategy. You will learn how to predict customer lifetime value and predict customer turnover using various methods. You will use customer data from a telecom company to predict churn, construct a recency-frequency-monetary dataset from an online retailer for customer lifetime value prediction, and build customer segments from product purchase data from a grocery shop.

Course Overview

projects-img

Virtual Labs

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Data Manipulation with pandas

Supervised Learning with scikit-learn

What You Will Learn

You will learn how to use different techniques to predict customer churn and interpret its drivers, measure, and forecast customer lifetime value, and finally, build customer segments based on their product purchase patterns

You will use customer data from a telecom company to predict churn, construct a recency-frequency-monetary dataset from an online retailer for customer lifetime value prediction, and build customer segments from product purchase data from a grocery shop

Course Instructors

Author Image

Karolis Urbonas

Head of Machine Learning and Science

Karolis is currently leading a Machine Learning and Science team at Amazon Web Services. He's a data science enthusiast obsessed with machine learning, analytics, neural networks, data cleaning, feat...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

Course Cover