Data Engineering and Data Integration Tools
Data Engineering for Beginners: Learn SQL, Python & Spark
★★★★★
$509.00 in stock
Udemy.com
as of October 11, 2026 5:26 pm
Master SQL, Python, and Apache Spark (PySpark) with Hands-On Projects using Databricks on Google Cloud
Created by:
Durga Viswanatha Raju Gadiraju
CEO at ITVersity and CTO at Analytiqs, Inc
CEO at ITVersity and CTO at Analytiqs, Inc
Created by:
Madhuri Gadiraju
Created by:
Pratik Kumar
Created by:
Phani Bhushan Bozzam
Aspiring Project Manager & Creative UI/UX Designer
Aspiring Project Manager & Creative UI/UX Designer
Created by:
Anushka Chakraborty
Rating:4.48 (5873reviews)
88071students 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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