Google Dataproc with PySpark - Beginner to Pro Course
Learn Google Cloud data processing with PySpark & Dataproc. ETL pipelines, real-world case studies, and hands-on experience. Master data workflows!
Course Content
Google Dataproc with PySpark - Beginner to Pro Course is an all-levels Udemy course taught by Saidhul Shaik. It runs 8h 38m, is taught in English, and includes a certificate of completion. Learners rate it 4.4 out of 5 from 6 reviews, with 50 students enrolled. It is a paid course, first published July 2025.
Ready to harness the power of Big Data on Google Cloud? This comprehensive course equips you with the skills to build scalable data processing pipelines using Apache Spark and Google Cloud Dataproc.
Dive into the fundamentals of Big Data and distributed processing, then master Apache Spark architecture and PySpark. You'll learn how Google Cloud Dataproc, Google's fully managed Spark and Hadoop service, revolutionizes cloud-native data processing.
This hands-on course guides you through the entire process, from setting up Dataproc clusters to developing and deploying PySpark-based ETL workloads. You'll gain expertise in:
- Big Data Concepts: Understand the challenges of Big Data and the necessity of distributed processing.
- Apache Spark & PySpark: Learn the architecture of Apache Spark and the fundamentals of PySpark programming.
- Google Cloud Dataproc: Master the setup and management of Dataproc clusters on Google Cloud.
- Data Manipulation: Work with RDDs, DataFrames, and advanced transformations using PySpark.
- ETL Processes: Perform efficient ETL tasks using real datasets on Dataproc.
- Pipeline Development: Build scalable, end-to-end batch pipelines integrating GCS (Google Cloud Storage) and BigQuery.
Through practical lab sessions and industry-inspired case studies from retail and healthcare, you'll gain experience in extracting, transforming, and loading data. You'll build a complete batch data pipeline from scratch to a production-ready state.
Key Features:
- Real-world case studies: Apply your skills to practical scenarios.
- Practical ETL labs: Hands-on experience with PySpark on Dataproc.
- Step-by-step cluster management: Learn to create and manage Dataproc clusters.
- Production-ready pipelines: Implement pipelines designed for real-world use.
- Industry-relevant assignments & quizzes: Reinforce your learning with practical assessments.
No prior experience with Big Data or Spark is required! This course is perfect for aspiring data engineers and cloud enthusiasts looking to build powerful data solutions on Google Cloud.
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