Overview
Context
The most successful companies today are the ones that know their customers so well that they can anticipate their needs.
In this Customer Segmentation in Python course offered by Data Camp, you will learn real-world techniques on customer segmentation and behavioral analytics, using a real dataset containing anonymized customer transactions from an online retailer.
You will first run cohort analysis to understand customer trends. You will then learn how to build easy to interpret customer segments. On top of that, you will prepare the segments you created, making them ready for machine learning.
Finally, you will make your segments more powerful with k-means clustering, in just few lines of code! By the end of this course, you will be able to apply practical customer behavioral analytics and segmentation techniques.
Programme Structure
Chapters
- Cohort Analysis
- Recency, Frequency, Monetary Value analysis
- Data pre-processing for clustering
- Customer Segmentation with K-means
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Campus Location
- New York City, United States
Disciplines
Data Science & Big Data View 466 other Short Courses in Data Science & Big Data in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Supervised Learning with scikit-learn
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
-
Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions