Data Engineering for Beginners: Learn SQL, Python & Spark
2025-03-23
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Master SQL, Python, and Apache Spark (PySpark) with Hands-On Projects using Databricks on Google Cloud
What you’ll 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
Description
Who this course is for:
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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