Predicting Customer Churn With R: A Practical Course

Enroll in this Free Udemy Course on Predicting Customer Churn with R. Start boosting customer retention today!

Dive into the world of customer retention with our hands-on course on predicting churn using RStudio. This comprehensive Udemy course guides you through every step of building a complete model for customer churn prediction. You’ll start with an understanding of what churn is, why it occurs, and how it directly impacts business profitability. You’ll explore essential retention metrics and analyze examples from various industries, appreciating the practical value these models can bring to your strategies.

As the course progresses, you’ll work with real customer datasets, learning how to clean, transform, and explore data with powerful tools like dplyr and ggplot2. You’ll identify relevant patterns, create derived variables—including RFM—and prepare your data for modeling by following best practices in data analysis. The hands-on training continues as you train multiple churn models using caret, comparing logistic regression and random forest, while applying cross-validation, grid search, and avoiding common pitfalls like leakage and overfitting.

In the final stages, you will learn how to interpret your model’s results and effectively present your findings to stakeholders. Discover how to leverage these predictions to design impactful retention campaigns. By the end of the course, you’ll have a functional model ready for real-world application, enhancing your expertise in customer retention strategies.

What you will learn:

  • Understand what churn is, how it is measured, and its impact on business profitability.
  • Clean and analyze real customer data in R, creating essential variables for the model.
  • Train and evaluate churn models with caret, applying best practices like cross-validation and hyperparameter selection.

Course Content:

  • Sections: 7
  • Lectures: 35
  • Duration: 3h 35m

Requirements:

  • No prior experience in machine learning is needed.
  • Basic knowledge of data analysis is recommended, along with familiarity with R.

Who is it for?

  • Analysts
  • Marketing professionals
  • CRM teams
  • Anyone interested in understanding and predicting customer churn using real data.
  • Beginners who want to learn how to build churn models in R.

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