Apache Spark 3 - Spark Programming in Python for Beginners (Udemy.com)

Data Engineering using Spark Structured API

( 98 Reviews )

Created by: Prashant Kumar Pandey

Produced in 2021

What you will learn

Apache Spark Foundation and Spark Architecture
Data Engineering and Data Processing in Spark
Working with Data Sources and Sinks
Working with Data Frames and Spark SQL
Using PyCharm IDE for Spark Development and Debugging
Unit Testing, Managing Application Logs and Cluster Deployment

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 94 / 100

Course Description

This course does not require any prior knowledge of Apache Spark or Hadoop. We have taken enough care to explain Spark Architecture and fundamental concepts to help you come up to speed and grasp the content of this course.
About the CourseI am creating Apache Spark 3 - Spark Programming in Python for Beginners course to help you understand the Spark programming and apply that knowledge to build data engineering solutions. This course is example-driven and follows a working session like approach. We will be taking a live coding approach and explain all the needed concepts along the way.
Who should take this Course?
I designed this course for software engineers willing to develop a Data Engineering pipeline and application using the Apache Spark. I am also creating this course for data architects and data engineers who are responsible for designing and building the organizations data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Spark implementation. Still, they work with the people who implement Apache Spark at the ground level.
Spark Version used in the CourseThis Course is using the Apache Spark 3.
x. I have tested all the source code and examples used in this Course on Apache Spark 3.
0.
0 open-source distribution.
Who this course is for:
Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache SparkProgrammers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

Time: 6h

Instructor Details

Prashant Kumar Pandey

4.7 Rating
98 Reviews

Prashant Kumar Pandey is passionate about helping people to learn and grow in their career by bridging the gap between their existing and required skills. In his quest to fulfill this mission, he is authoring books, publishing technical articles, and creating training videos to help IT professionals and students succeed in the industry.
With over 18 years of experience in IT as a developer, architect, consultant, trainer, and mentor, he has worked with international software services organizations on various data-centric and Bigdata projects.
Prashant is a firm believer in lifelong continuous learning and skill development. To popularize the importance of lifelong continuous learning, he started publishing free training videos on his YouTube channel and conceptualized the idea of creating a Journal of his learning under the banner of Learning Journal.
He is the founder, lead author, and chief editor of the Learning Journal portal that offers various skill development courses, training, and technical articles since the beginning of the year 2018.

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Reviews

4.7

98 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Yuki Kudo on 11/21/2020

This was the best course for start learning Spark

By Prag Tyagi on 11/14/2020

This is by far the best course on Spark on Udemy . I wanted to give 5 star but refrained from the same because of following reasons :-
i)RDD is not explained in detail. Although all product companies ask for the same in interviews
ii)The standard configuration which one should set in the driver script , For Ex :- no of executors , memory per executor and no of cores per executor is not explained in detail . That should be covered .
But apart from these points this course explains in detail how you can optimize your spark script to the maximum . Kudos to the tutor for this amazing course . Looking forward to start my spark streaming course.

By Kumar Rahul on 11/14/2020

This course covers several advanced topics like handling un structured data , unit testing of spark application , logging , understanding of spark logs very well.
Thanks for creating this tutorial.

By Rom on 11/14/2020

Good course that goes thru most of spark and python fundamentals on beginner level.

By Eric Everhard on 11/14/2020

Yes

By Mallikarjuna Tm on 11/14/2020

one of the best course for learning pyspark

By Bhikshalu Moka on 11/14/2020

Training is good.
Felt little fast during confugurations etc.
I want to learn more transformations . Please suggest a course that gives me more knowledge on ETL processes using Pyspark
To perform complex calculations , unions etc

By Sridhar Nakka on 11/14/2020

theoretical demo is good but while coding give some explanation or material tagged to videos to enable us to write the code ourself

By Nabjiban Pattnaik on 11/14/2020

Fundamentally Brilliant course. Will make anyone's foundation in Spark quite strong.

By V J on 11/7/2020

Great Introduction about Data Lake and the significance of Spark & other Data ecosystem.

By Carlo Jumagdao on 11/7/2020

This spark course is awesome. Learned a lot of things!

By Shrey Khabya on 11/1/2020

The course pre-requisite was just the basic knowledge of python but the instructor is going very fast while skipping the explanation of many of the configuration settings that are required to run any pyspark code or for that matter setting up the cluster also.
I am not sure if these skipped explanations will be taken care in future lectures or not.
Also, the pace of this course is very fast for a beginner to understand basic concepts, leave aside the complex one's.
Instructor is copy pasting commands in the videos everywhere, which is hard to cope up with in real time understanding for a beginner.
I am already in Section-3 and I know nothing about the codes that have been used till now.
This course is just turning out to be a theory lecture instead of practical implementations of Spark.
Really disappointed till now.