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Big Data Engineering in PySpark Certification Training Course Subjects/Syllabus
The Online PySpark Certification Training Course curriculum may differ based on the program or training provider. However, the following is a rough description of the subjects that are commonly taught in the course:
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Introduction to Big Data Hadoop and Spark |
Introduction to Python for Apache Spark |
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Functions, OOPs, and Modules in Python |
Deep Dive into Apache Spark Framework |
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Playing with Spark RDDs |
DataFrames and Spark SQL |
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Machine Learning using Spark MLlib |
Deep Dive into Spark MLlib |
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Understanding Apache Kafka and Apache Flume |
Apache Spark Streaming - Processing Multiple Batches |
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Apache Spark Streaming - Data Sources |
Implementing an End-to-End Project |
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FAQ's
Let's clear up some doubts
While basic programming expertise is advantageous, the course focuses on the core Python principles required for PySpark development.
Yes, the course accepts students from various backgrounds interested in data analytics and Spark programming.
Yes, companies worldwide widely acknowledge the certification, verifying your knowledge of PySpark programming.
A minimum of 10+2 education or equivalent is required; no special technical requirements are necessary.
You will earn a PySpark certification from the training provider after completing the course and examinations.
Professional professors often teach the sessions in real-time, allowing for real-time interaction and participation.
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