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PySpark - Apache Spark Programming for Beginners (2026)

Name: PySpark - Apache Spark Programming for Beginners (2026)
Price: 89.99 USD
Availability: InStock
Rating: 4.6 (17007 reviews)

4.6(17,007)106k studentsALL LEVELSEnglish

Korshub's take

Spark for data engineers and architects

Apache Spark powers data pipelines at scale, but jumping in without a roadmap is disorienting. This course takes a live-coding approach—you see examples and build intuition as you go, without needing prior Spark or Hadoop knowledge. The material applies to multiple roles: software engineers building data solutions, data architects designing infrastructure, even non-technical managers overseeing Spark teams.

All examples are tested on Apache Spark 4.1 in a Databricks environment, so you're learning current practice, not outdated patterns.

About this course

This course does not require any prior knowledge of Apache Spark or Hadoop. We have taken sufficient care to explain the fundamental concepts of Spark, helping you come up to speed and grasp the content of this course.

About the Course

I am creating the PySpark - Apache Spark Programming for Beginners course to help you understand Spark programming and apply that knowledge to build data engineering solutions. This course is example-driven and follows a working session-like approach. We will take a live coding approach and explain all the necessary concepts along the way.

Who should take this Course?

I designed this course for software engineers willing to develop a Data Engineering pipeline and application using Apache Spark. I am also creating this course for data architects and data engineers who are responsible for designing and building the organisation’s data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Spark implementation. Still, they work with the people who implement Apache Spark at the ground level.

Spark Version used in the Course

This Course is using Apache Spark 4.1. I have tested all the source code and examples used in this Course on Apache Spark 4.1 in the Databricks environment.