Data Processing with PySpark is a course or training program that focuses on teaching individuals how to process large data sets using Apache Spark and PySpark, a Python library for Apache Spark. The course covers the basics of Spark and its architecture, as well as how to perform common data processing tasks such as data filtering, aggregation, and transformation using PySpark. The course also covers advanced topics such as working with Spark data frames, machine learning with Spark, and deployment and scaling of Spark applications. The target audience for this course is data engineers, data scientists, and software developers who want to work with large data sets in a distributed computing environment. The prerequisites for this course include a basic understanding of Python programming, SQL, and familiarity with data processing concepts.
Target Audience:
Learning Objectives:
The 1-on-1 Advantage
Flexible Dates
4-Hour Sessions
Live Online Training (Duration : 32 Hours) | |||
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