Udemy Coupon - Data Engineering Essentials using SQL, Python, and PySpark

Learn key Data Engineering Skills such as SQL, Python, Apache Spark (Spark SQL and Pyspark) with Exercises and Projects-56 hours course

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.

This course is designed to address these key challenges for professionals at all levels to acquire the required Data Engineering Skills (Python, SQL, and Apache Spark).

Setup Environment to learn Data Engineering Essentials such as SQL (using Postgres), Python, etc.
Setup required tables in Postgres to practice SQL
Writing basic SQL Queries with practical examples using WHERE, JOIN, GROUP BY, HAVING, ORDER BY, etc
Advanced SQL Queries with practical examples such as cumulative aggregations, ranking, etc
Scenarios covering troubleshooting and debugging related to Databases.
Performance Tuning of SQL Queries
Exercises and Solutions for SQL Queries.
Basics of Programming using Python as Programming Language
Python Collections for Data Engineering
Data Processing or Data Engineering using Pandas
2 Real Time Python Projects with explanations (File Format Converter and Database Loader)
Scenarios covering troubleshooting and debugging in Python Applications
Performance Tuning Scenarios related to Data Engineering Applications using Python
Getting Started with Google Cloud Platform to setup Spark Environment using Databricks
Writing Basic Spark SQL Queries with practical examples using WHERE, JOIN, GROUP BY, HAVING, ORDER BY, etc
Creating Delta Tables in Spark SQL along with CRUD Operations such as INSERT, UPDATE, DELETE, MERGE, etc
Advanced Spark SQL Queries with practical examples such as ranking
Integration of Spark SQL and Pyspark
In-depth coverage of Apache Spark Catalyst Optimizer for Performance Tuning
Reading Explain Plans of Spark SQL Queries or Pyspark Data Frame APIs
In-depth coverage of columnar file formats and Performance tuning using Partitioning

How to Enroll Data Engineering Essentials using SQL, Python, and PySpark course?

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How many members can access this course with a coupon?

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