Are you ready to master Apache Spark by working on a real-world Machine Learning project? This course will take you step by step through building a Telecom Customer Churn Prediction model using Apache Spark ML.

Customer churn is one of the biggest challenges in the telecom industry. Companies invest heavily to retain their customers, and predictive analytics plays a crucial role in identifying which customers are likely to leave. In this hands-on course, you’ll learn how to use Big Data and Spark ML to solve this real-world problem with an end-to-end project.

You will begin with the basics of Spark and Machine Learning, setting up your Spark cluster in Databricks (no local installation needed), and learning how to work with DataFrames and notebooks. Then, we’ll dive deep into the churn dataset, perform data exploration, and build a machine learning pipeline for churn prediction.

By the end of this course, you will have the skills, confidence, and project experience to apply Spark ML techniques to real-world business problems—not only in telecom but across other industries like finance, e-commerce, and healthcare.

This course is designed to be practical and project-focused, ensuring that you learn by doing, with clear explanations and real examples every step of the way.

What makes this course unique?

• Real-world Telecom Churn Prediction Project

Key Skills You Will Gain

• Understanding Spark basics (clusters, notebooks, and DataFrames)