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This course assumes no prior Spark or Hadoop knowledge and introduces the architecture and fundamentals before writing code. The approach is example-driven and works like a session with an instructor at the keyboard, with concepts explained as they come up.
Software engineers building data engineering pipelines are the main audience. Data architects and engineers who design data infrastructure will also find the architecture material relevant, and engineering managers who oversee Spark work may use it to understand what their teams do.
The examples were tested on Spark 4.0.1, so check your installed version if you follow along on another release.
This course does not require any prior knowledge of Apache Spark or Hadoop. We have taken enough care to explain Spark Architecture and fundamental concepts to help you come up to speed and grasp the content of this course.
About the Course
I am creating Apache Spark Programming in Scala 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 be taking a live coding approach and explaining all the needed 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.x. I have tested all the source code and examples used in this Course on Apache Spark 4.0.1 and the Spark Connect environment.
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Data Engineering, Big Data, and Machine Learning on GCP
