Customer Analytics

Course Description

This course combines a few most applicable use cases of modeling behavior of customers. It includes churn modeling, campaign optimization, CLV modeling, customer segmentation, applications of graph modeling with real-life examples from banking, (e)retail, telecom. This course expects basic knowledge of ML/data science concepts and exposure to marketing functions of organizations.

Course tools

  • Python
  • R
  • Power BI

Prerequisites

  • Data manipulation basics
  • Marketing basics

Level of complexity of course

Advance

Lecturer

Mr. Liubomyr Bregman
Amazon EU

Liubomyr is a Data science team lead with experience in multiple industries as a consultant and expert. Currently, he is employed in Amazon EU in Luxembourg where Liubomyr leads the development and product management of a few complex network forecasting tools for the needs of the supply chain. Previously he served as a data science consultant of banks, fin sector, telecom, and retail companies in PwC Data Analytics.

Fields of interests: Anomaly detection, Causal ML, Networks

Contacts: [email protected]