PySpark – Apache Spark Programming in Python for beginners

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Last updated on November 20, 2024 6:08 pm
PySpark – Apache Spark Programming in Python for beginners
PySpark – Apache Spark Programming in Python for beginners

Description

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Data Engineering Essentials using SQL, Python, and PySpark

★★★★★
$109.99  in stock
Udemy.com
as of November 20, 2024 6:08 pm

Learn key Data Engineering Skills such as SQL, Python, Apache Spark (Spark SQL and Pyspark) with Exercises and Projects

Created by: Durga Viswanatha Raju Gadiraju
CEO at ITVersity and CTO at Analytiqs, Inc
Created by: Madhuri Gadiraju
Created by: Pratik Kumar
Created by: Sathvika Dandu
Created by: Sai Varma
Created by: Phani Bhushan Bozzam
Aspiring Project Manager & Creative UI/UX Designer
Rating:4.4 (5326reviews)     82188students enrolled

What Will I Learn?

  • Setup Environment to learn SQL and Python essentials for Data Engineering
  • Database Essentials for Data Engineering using Postgres such as creating tables, indexes, running SQL Queries, using important pre-defined functions, etc.
  • Data Engineering Programming Essentials using Python such as basic programming constructs, collections, Pandas, Database Programming, etc.
  • Data Engineering using Spark Dataframe APIs (PySpark) using Databricks. Learn all important Spark Data Frame APIs such as select, filter, groupBy, orderBy, etc.
  • Data Engineering using Spark SQL (PySpark and Spark SQL). Learn how to write high quality Spark SQL queries using SELECT, WHERE, GROUP BY, ORDER BY, ETC.
  • Relevance of Spark Metastore and integration of Dataframes and Spark SQL
  • Ability to build Data Engineering Pipelines using Spark leveraging Python as Programming Language
  • Use of different file formats such as Parquet, JSON, CSV etc in building Data Engineering Pipelines
  • Setup Hadoop and Spark Cluster on GCP using Dataproc
  • Understanding Complete Spark Application Development Life Cycle to build Spark Applications using Pyspark. Review the applications using Spark UI.

Requirements

  • Laptop with decent configuration (Minimum 4 GB RAM and Dual Core)
  • Sign up for GCP with the available credit or AWS Access
  • Setup self support lab on cloud platforms (you might have to pay the applicable cloud fee unless you have credit)
  • CS or IT degree or prior IT experience is highly desired

Target audience

  • Computer Science or IT Students or other graduates with passion to get into IT
  • Data Warehouse Developers who want to transition to Data Engineering roles
  • ETL Developers who want to transition to Data Engineering roles
  • Database or PL/SQL Developers who want to transition to Data Engineering roles
  • BI Developers who want to transition to Data Engineering roles
  • QA Engineers to learn about Data Engineering
  • Application Developers to gain Data Engineering Skills

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