Udemy – GCP Dataproc – Basics to Advanced – Case studies & Pipelines

In this hands-on course, you’ll go from the fundamentals of Big Data and Apache Spark to mastering Google Cloud Dataproc, Google’s fully managed Spark and Hadoop service. Whether you’re an aspiring data engineer or a cloud enthusiast, this course will help you learn how to develop and deploy PySpark-based ETL workloads on Dataproc using real-world case studies and end-to-end pipeline projects.

We start with the basics — understanding Big Data challenges, Spark architecture, and why Dataproc is a game-changer for cloud-native processing. You’ll learn how to create Dataproc clusters, write and run PySpark code, and work with RDDs, DataFrames, and advanced transformations.

Key Features:

• Real-world case studies from retail and healthcare domains
• Practical ETL labs using PySpark on Dataproc
• Step-by-step cluster creation and management
• Production-style batch pipeline implementation
• Industry-relevant assignments and quizzes
• No prior experience in Big Data or Spark required

• Aspiring Data Engineers
• Anyone Preparing for GCP Data Engineer Certifications