What you'll learn:
- Apache Spark Programming in Python (PySpark)
- Spark Programing in Databricks Free Account
- Working with Data Frames Transformations and Actions
- Handling Schema and working with different data types
- Working with Complex Data Types, Aggregation, Joins and UDF
- Working with Data Sources and Sinks
- Unit Testing and Data Engineering Techniques
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.
