PySpark Foundation for Data Engineering | Beginners
Data Engineering, PySpark, Coding exercise
Updated on Sep, 2023
Language - English
Course Description
This course will prepare you for a real world Data Engineer role !
Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.
In this course we will get to know and apply few of the most essential and basic functions in PySpark, that are used frequently in scripting for any project based on PySpark.
About PySpark:
Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!
What you will learn :
SparkSession and imports
Spark DataFrame and its characteristics
Syntax and example
Print results
Understanding the data
Number of records
Columns in dataFrame
Describe a DataFrame
Schema of a DataFrame
Create a new column
Arithmetic operations on Data
Change column data type
Create a column with integer as constant
Apply what we know
Rounding of digits
Sorting operation
Drop columns
Rename columns
Create a column with string as constant
Conditional Statements
Changing case of a column
Filter operations
Grouping and aggregations
Who this course is for:
Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
Big data beginners who want to learn how to code in the real world
Aspiring candidates for data engineering role
Goals
What will you learn in this course:
- This course will prepare you for a real world Data Engineer role !
- Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.
- In this course we will get to know and apply few of the most essential and basic functions in PySpark, that are used frequently in scripting for any project based on PySpark.
Prerequisites
What are the prerequisites for this course?
Some basic programming skills (Not Mandatory)
Will to implement theoretical knowledge in pratical.
Curriculum
Check out the detailed breakdown of what’s inside the course
Lets Begin!
24 Lectures
-
Introduction to the course
02:20
02:20
-
SparkSession and Imports
03:12
03:12
-
Spark DataFrame and its characteristics
02:01
02:01
-
Syntax and example
07:09
07:09
-
Print operation
00:44
00:44
-
Understanding the data
00:19
00:19
-
Number of records in DataFrame
00:27
00:27
-
Columns present in DataFrame
00:30
00:30
-
Summary of a DataFrame
01:03
01:03
-
Get schema of a DataFrame
00:53
00:53
-
Create a new column in a dataframe
04:53
04:53
-
Arithmetic operations on columns
05:27
05:27
-
Change column Data Types by casting
04:19
04:19
-
Create a column with integer constant
01:52
01:52
-
Application of the learnings
01:31
01:31
-
Rounding operations using bround
03:46
03:46
-
Sorting operation
05:24
05:24
-
Drop columns of a dataframe
04:51
04:51
-
Rename a column.
03:23
03:23
-
Create a column with String constant
01:14
01:14
-
Conditional Statements
04:46
04:46
-
Changing Case of a column
01:49
01:49
-
Filter operations
03:24
03:24
-
Grouping and Aggegrations
08:27
08:27
Instructor Details
Akash Pawar
Akash Pawar is a Certified Google cloud Associate engineer. He has completed Bachelor of Technology in Electronics Engineering from National Institute of Technology (NIT, Rourkela) and has years of experience as a professional data engineer and trainer for ETL operations using PySpark. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data engineering to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Data Engineer in Fractal Analytics.
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