Customer Analytics in Python
This course is the perfect way to stand out from the crowd and acquire a rare and highly valuable skillset. Customer Analytics in Python is a comprehensive course that covers the most exciting methods used by companies, all implemented in Python. With the help of 3 experienced instructors, you will learn about the marketing fundamentals, cluster analysis, dimensionality reduction, descriptive statistics, elasticity modeling, and deep learning. Through this course, you will gain the knowledge and skills to perform customer analytics and make accurate predictions about customer behavior. ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
Paid Certification
Language:
English
Start Date:
2020-11-02
Course Overview
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Updated in [July 18th, 2023]
This course, Customer Analytics in Python, is the perfect way to distinguish yourself with a rare and extremely valuable skillset. It covers some of the most exciting methods used by companies, all implemented in Python. The course is divided into 5 major parts, each of which will have its strong sides and shortcomings. The course author, Nikolay Georgiev, is a Ph.D. who has focused on marketing analytics during his academic career and has gained significant practical experience while working as a consultant on numerous world-class projects.
In the first part, students will be introduced to the relevant theory needed to start performing customer analytics. The second part will cover cluster analysis and dimensionality reduction to help students segment their customers. The third part consists of applying descriptive statistics as the exploratory part of the analysis. The fourth part will engage with elasticity modeling for purchase probability, brand choice, and purchase quantity. Finally, the fifth part will leverage the power of Deep Learning to predict future behavior.
Throughout the course, students will be working with several popular packages such as NumPy, SciPy, and scikit-learn. They will also be able to visualize the data appropriately to build their understanding of the methods even further.
This course is created by 3 instructors working closely together to provide the most beneficial learning experience. With 550,000+ students here on Udemy, the best education requires a remarkable teaching collective and a practical approach. This course provides both.
Course Syllabus
Introduction
A Brief Marketing Introduction
Setting up the Environment
Segmentation Data
Hierarchical Clustering
K-Means Clustering
K-Means Clustering based on Principal Component Analysis
Purchase Data
Descriptive Analyses by Segments
Modeling Purchase Incidence
Modeling Brand Choice
Modeling Purchase Quantity
Deep Learning for Conversion Prediction
Pros & Cons
Practical and complete: Users appreciate that the course provides practical knowledge and covers a wide range of topics related to customer analytics. Excellent explanation of concepts: Users find the explanations of concepts related to demand and elasticity outstanding and valuable.
Buggy and messy code: Some users complain about the code being buggy and messy, making it difficult to follow along and generalize the skills learned in the course. Fast-paced coding: A few users find the coding parts of the course to be too fast, making it challenging to keep up without pausing the videos frequently.
Course Provider
Provider Udemy's Stats at AZClass
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