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PySpark - Apache Spark Programming for Beginners (2026) (Udemy.com)

Master Apache Spark Programming in Python (PySpark) Using Databricks Free Edition - Recreated for 2026

4.7
17,491 reviews

Created by: Prashant Kumar Pandey

Last updated January 2026

Our take

Based on the ratings of 17,491 students, a sample of their written reviews and the syllabus, as the course stood in January 2026. No course pays to be reviewed.

A PySpark course built around the DataFrame API, rebuilt for 2026 so the examples run on Databricks Free Edition. The syllabus shows 81 lectures over about 28.5 hours: Spark architecture first, then schemas, transformations, data types, joins, aggregations, UDFs and unit testing, a section on running Spark from a laptop IDE, and a capstone project near the end. It assumes you already write Python and SQL, so it is a beginner course in Spark, not in programming. Data engineers and software developers moving onto Spark are the stated target audience.

Students praise Prashant Kumar Pandey's teaching more than anything else. Reviewers describe his pace as calm and measured, his explanations as detailed, and the material as well structured, with plenty of worked examples. The complaints are smaller but real. One reviewer finds the repetition tiresome, saying he explains the same point several times when a rewind would do. One three-star review wishes the supplied notebooks were not already filled in, which takes the challenge out of the early sections. There are also scattered reports of playback trouble and missing audio, and the course has no quizzes or coding exercises to check progress against.

The January 2026 refresh matters here, because older Spark courses show their age fast. Two sections of older videos are still in the syllabus, labelled as such, so expect a bit of overlap. Of the courses it sits beside in the Hadoop group, it is one of the Python options; pick it over the Scala and wider Hadoop courses if the DataFrame API is what you need. Recommended for anyone with Python and SQL who wants a patient, thorough route into Spark.

Best forPython developers with some SQL who want to learn Spark's DataFrame API properly before taking on data engineering work.
Skip it ifYou want Scala, the broader Hadoop ecosystem, or a course with quizzes and graded exercises to check progress.

Pros

  • Rebuilt for 2026 and runs on Databricks Free Edition, so there is no local Spark install to fight with
  • Reviewers single out the calm pace and detailed explanations; concepts come before the code
  • Deep coverage of DataFrame transformations, data types, joins, aggregations, UDFs and unit testing
  • Ends with a capstone project of about three hours plus a section on running Spark from a laptop IDE

Cons

  • One reviewer finds the repetition excessive; the same point is often explained more than once
  • Supplied notebooks arrive already completed, which removes the practice from the early sections
  • No quizzes or coding exercises, and two sections of older videos remain in the syllabus
I really like Mr. Pandey's classes. His teaching pace is perfect, and his calm tone makes it easy to follow along without feeling overwhelmed.
Song Jang, a student

Listed as all levels, but it assumes working Python and SQL; it is a Spark beginner course, not a programming one.

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What you will learn

  • Apache Spark Programming in Python (PySpark)
  • Spark Programing in Databricks Free Account
  • Working with Data Frames Transformations and Actions
  • Handling Schema and working with different data types
  • Working with Complex Data Types, Aggregation, Joins and UDF
  • Working with Data Sources and Sinks
  • Unit Testing and Data Engineering Techniques

Course content

14 sections · 81 lectures · 28 hours of video 3 articles

  1. 1Understanding Big Data and Distributed Data Processing 1 free preview3 lectures · 1.2 hours
  2. 2Introduction to Apache Spark7 lectures · 1.1 hours
  3. 3Getting Started with Spark Programming6 lectures · 2.9 hours
  4. 4Spark Data Types and Schema4 lectures · 2.2 hours
  5. 5Dataframe Transformations6 lectures · 3.5 hours
  6. 6Working with different data types9 lectures · 5.1 hours
  7. 7Joins in Spark Dataframe5 lectures · 2.4 hours
  8. 8Aggregations in Spark Dataframe4 lectures · 1.7 hours
  9. 9UDF and Unit Testing4 lectures · 1.9 hours
  10. 10Spark On Your Laptop IDE3 lectures · 1.7 hours

Who it is for

The instructor says it suits

  • Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
  • Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

What you need before you start

  • Programming Knowledge Using Python Programming Language
  • SQL Programming Knowledge

How it compares

Against the other 150 rated Udemy courses in Hadoop on CourseDuck:

  • Rating4.7 out of 5higher than 91% of them
  • Reviews17,491#4 of 151 by number of reviews
  • Length28.5 hourslonger than 94% of them
  • Last updatedJanuary 2026more recently than 78% of them

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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
Read More All Levels All Levels product length iconTime: 28.5h

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Instructor Details

Prashant Kumar Pandey

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

17,491 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

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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.

Showing 12 of 98 reviews

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Overall Score : 94 / 100

PySpark - Apache Spark Programming for Beginners (2026)
Visit course on Udemy Write a review
  • Video Duration: icon 28.5h
  • Price: $89.99
  • Provider: icon Udemy
  • Updated: icon January 2026
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
  • Lectures:81 in 14 sections
  • Students:110,800
  • Udemy badge:Bestseller
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