Customer Segmentation in Python

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

The most successful companies are those that can anticipate their customers' needs. Data analysts are crucial to unlocking deep insights and segmenting customers in order to better serve them. This course will show you how to segment customers and conduct behavioral analysis using anonymous customer transactions obtained from an online retailer. You will first do a cohort analysis to understand customer trends. Next, you'll learn how to create customer segments that are easy to understand. The segments you create for machine learning will be prepared. You can strengthen your segments with k-means clustering in just a few lines. This course will show you how to segment customers and use customer behavior analytics.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Supervised Learning with scikit-learn

Data Manipulation with pandas

What You Will Learn

Finally, you will make your segments more powerful with k-means clustering, in just few lines of code!

In this course, you will learn real-world techniques on customer segmentation and behavioral analytics, using a real dataset containing anonymized customer transactions from an online retailer

Learn how to segment customers in Python

You will first run cohort analysis to understand customer trends. You will then learn how to build easy to interpret customer segments

Course Content

Expand all sections

Module 1: Recency, Frequency, Monetary Value analysis

Module 2: Data pre-processing for clustering

Module 3: Customer Segmentation with K-means

Module 4: Cohort Analysis

Course Instructors

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...