This course focuses on building a predictive churn model in the field of data science. By the end of the course, learners will be able to develop, evaluate, deploy, monitor, and improve predictive models. The course teaches skills such as data preparation, encoding, model development, evaluation, and deployment. The teaching method includes case studies, hands-on exercises, and a final exam. This course is intended for individuals interested in data science, predictive modeling, and improving business outcomes through data analysis.
Data Science in Action - Building a Predictive Churn Model
via SAP Learning
This course may be unavailable.
Overview
Syllabus
Week 1: Case Study Introduction
Week 2: Prepare and Encode Data
Week 3: Develop, Evaluate, and Deploy Models
Week 4: Monitor Models and Improve Performance
Week 5: Final Exam
Taught by
Stuart Clarke
