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Best Hands-on Big Data Practices with PySpark & Spark Tuning (Udemy.com)

Semi-Structured (JSON), Structured and Unstructured Data Analysis with Spark and Python & Spark Performance Tuning

Created by: Amin Karami

Last updated November 2025

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What you will learn

  • Understand Apache Spark’s framework, execution and programming model for the development of Big Data Systems
  • Learn step-by-step hands-on PySpark practices on structured, unstructured and semi-structured data using RDD, DataFrame and SQL
  • Learn how to work with a free Cloud-based and a Desktop computer for Spark setup and configuration
  • Build simple to advanced Big Data applications for different types of data (volume, variety, veracity) through real case studies
  • Investigate and apply optimization and performance tuning methods to manage data Skewness and prevent Spill
  • Investigate and apply Adaptive Query Execution (AQE) to optimize Spark SQL query execution at runtime
  • Investigate and be able to explain the lazy evaluations (Narrow vs Wide transformation) and internal working of Spark
  • Build and learn Spark SQL applications using JDBC (Java Database Connectivity)

How it compares

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

  • Rating4.3 out of 5higher than 43% of them
  • Reviews1,668#41 of 151 by number of reviews
  • Length13.1 hourslonger than 79% of them
  • Last updatedNovember 2025more recently than 76% of them

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Course Description

In this course, students will be provided with hands-on PySpark practices using real case studies from academia and industry to be able to work interactively with massive data. In addition, students will consider distributed processing challenges, such as data skewness and spill within big data processing. We designed this course for anyone seeking to master Spark and PySpark and Spread the knowledge of Big Data Analytics using real and challenging use cases.

We will work with Spark RDD, DF, and SQL to process huge sized of data in the format of semi-structured, structured, and unstructured data. The learning outcomes and the teaching approach in this course will accelerate the learning by Identifying the most critical required skills in the industry and understanding the demands of Big Data analytics content.

We will not only cover the details of the Spark engine for large-scale data processing, but also we will drill down big data problems that allow users to instantly shift from an overview of large-scale data to a more detailed and granular view using RDD, DF and SQL in real-life examples. We will walk through the Big Data case studies step by step to achieve the aim of this course.

By the end of the course, you will be able to build Big Data applications for different types of data (volume, variety, veracity) and you will get acquainted with best-in-class examples of Big Data problems using PySpark.

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Instructor Details

Amin Karami

Dr. Amin Karami is an Associate Professor in the School of Computer Science and Digital Technologies (CDT) at ACE. His main role involves leading the PG courses and being the course leader for MSc Big Data Technologies.

Internally, Dr. Karami has spearheaded innovative programs that promote diversity and inclusion in STEM fields. By securing £1.23 million in funding from the Office for Students, he has developed groundbreaking MSc AI and Data Science courses tailored for far-STEM and non-STEM graduates in 2023-25. His commitment to fostering diversity is evident in his efforts to recruit underrepresented groups.

External roles

Dr. Karami plays a vital role as an external examiner and collaborates with prestigious organisations such as Multiverse and Cambridge Spark. His work with these institutions focuses on enhancing educational quality and aligning academic programs with industry needs. Additionally, he has been recognized with the UEL Vice-Chancellor & President Impact & Innovation Award for Industry 4.0 readiness in 2023. Dr. Karami has organised successful events like the Chainlink Bootcamp, bridging academia and industry, and served as a guest editor for high-impact international journals. His dedication to professional development is further demonstrated by his Fellow of the Higher Education Academy (FHEA) certification and his role as a program chair at international conferences.

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Reviews

4.3

1,668 ratings on Udemy

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By Zareen Khan on 12/27/2025

cant retake the assignment

By Isabella Julia k on 11/28/2025

This course finally helped me understand real Big Data workflows using PySpark. The hands-on examples are practical, and the Spark tuning section cleared up so many doubts I had from before.

By Akash Sharma on 1/12/2025

presentation during explanation could be better, the text was never understandable during explanations and this is something that can be improved. overall, the quality of the content and instructor knowledge was commendable.

By Sanjit Paul on 6/18/2023

This course really helps to get good hands-on experience on working with various types of data including Structured, Semi-Structured, Un-Structured data. Along with that it also has some of the optimization technique which are really helpful. Thank you Amin for this course.

By Vish Raj on 6/16/2023

This was an amazing course about Spark. I have taken other Spark courses where they teach you the mechanics of using Spark and talk a bit about the architecture and this course does a great job of diving deep into practical concepts that will get used in your day to day job. Also a learnt some interesting optimization techniques that I did not know before.

By Anonymized User on 4/24/2023

100% useful course so far in udemy. I enrolled in a couple of courses related to pyspark but none of them helped me in practical application. But this course has the most practical explanation of optimizations using rdd,dataframes. Also went through spark UI which has tasks performance, jobs/stages/plans analysis. This is what 99% courses are missing but this one is the most practical and helpful to me. Now I truly confidential in attending data engineering interviews all thanks to the instructor and udemy. Most humble moment.

By Eugenio Cano Serrano on 4/5/2023

Best PySpark course I have ever done. It blends theory and practice perfectly. It really helped me to understand why you have to do calculations like that while working with RDDs that I completely missed in other courses. The assignments are challenging and checked by the instructor. It took my theoretical and practical PySpark knowledge to the level that I needed.

By Jade Nguyen on 2/9/2023

Had a chance to connect with Amin on LinkedIn. He's super friendly. I love this Spark course since he explains Spark concepts and its application very down to earth. Even though each session is long (1 hour or so), but I can learn the how to trouble shoot issues and apply the best practices. In addition, Amin is very responsive to students' question. I asked some question that requires some explanation on the course video, and Amin was willing to set up a Zoom call with me to go over it. This teacher student interaction is rare for online courses. One of my best Spark courses so far! Glad that I chose it...

By Anonymized User on 11/30/2022

I really enjoyed entire course. Even though I am an intermediate spark professional I got to know various concepts in details with how to use that particular concepts in real-time projects. Recommend it for sure.

By Dron Adhikari on 8/21/2022

one of the best hands on course on pyspark, the hands-on activities are great and teach a lot of important topics with great amount of depth. The best part is the white-boarding which is used to explain the concepts in a step by step process which really makes the entire course rich with great explanations for the topics and their inner-workings and logics Great course!!

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Overall Score : 86 / 100