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: liubomyrb@gmail.com