Customer Analytics in Python

Introducing you to Customer Analytics with Python. You will learn the fundamentals of marketing, as well as the practical skills to analyze customer data and predict the purchase behavior of clients.

With Elitsa Kaloyanova and Nikolay Georgiev

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Course Overview

Customer Analytics in Python is where marketing and data science meet. Data science and marketing are two of the key driving forces that help companies create value and stay on top in today’s fast-paced economy. This course is packed with knowledge, and includes sections on customer and purchase analytics, as well as a deep-learning model, all implemented in Python.

60 High Quality Lessons
5 Practical Tasks
5 Hours of Video
Certificate of Achievement

Skills you will gain

data analysisdata processingfinancial analysismachine learningprogrammingpythontheory

What You'll Learn

This course will teach you how to gain authentic insights from the customer's data, as well as how to leverage the power of machine and deep learning to perform customer analytics. This is a highly valuable and rare skillset to have both in data analytics and data science.  

Perform K-means clustering
Apply Principal Components Analysis (PCA)
Combine PCA and K-means for customer segmentation
Model purchase incidence through probability of purchase elasticity
Complete the purchasing cycle by predicting purchase quantity elasticity 
Carry out a deep learning model with TensorFlow 2.0 to predict purchasing behavior

Curriculum

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“In this course, you will learn beginner and advanced customer analytics in Python: Marketing theory, PCA, K-means clustering, Elasticity modeling, and Deep neural networks. This is a learning journey that builds a bridge between marketing theory and practical implementation with Python.”

Nikolay Georgiev
Director at KBC Group

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Customer Analytics in Python

With Elitsa Kaloyanova and Nikolay Georgiev

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