PySpark - Apache Spark Programming in Python for beginners

Master Apache Spark Programming in Python (PySpark) Using Free Databricks Community for Beginners with Capstone Project

4.53 (12717 reviews)

Udemy

platform

English

language

Data Science

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

Course Gallery

PySpark - Apache Spark Programming in Python for beginners – Screenshot 1 — Screenshot 1 – PySpark - Apache Spark Programming in Python for beginners

PySpark - Apache Spark Programming in Python for beginners – Screenshot 2 — Screenshot 2 – PySpark - Apache Spark Programming in Python for beginners

PySpark - Apache Spark Programming in Python for beginners – Screenshot 3 — Screenshot 3 – PySpark - Apache Spark Programming in Python for beginners

PySpark - Apache Spark Programming in Python for beginners – Screenshot 4 — Screenshot 4 – PySpark - Apache Spark Programming in Python for beginners

Charts

Students

Price

Rating & Reviews

Enrollment Distribution

Comidoc Review

Our Verdict

Boasting over 75k subscribers and a strong 4.53-star rating, this PySpark course effectively teaches the basics while also covering advanced concepts in Data Engineering using Python. While organization and pacing may be improved slightly, it excels at engaging learners with real-world applications, hands-on projects, and Prashant Pandey's clear teaching style—making it a worthwhile investment for those seeking an accessible approach to mastering PySpark.

What We Liked

The course covers a comprehensive range of topics, providing a solid foundation in PySpark and Data Engineering principles.
Prashant Pandey's teaching style is clear and engaging, using simple language and practical examples to make complex topics accessible.
Hands-on projects reinforce concepts and help build skills gradually, with no pre-made notebooks available to promote genuine learning.
Real-world applications and historical context of Spark contribute to a rich learning experience, inspiring further exploration in Data Engineering.

Potential Drawbacks

The course's organization and pacing might be improved, as some reviewers found the sequence of topics confusing or overwhelming.
Some sections may not directly address the needs of beginners looking for practical Spark usage; instead focusing on internal workings and history.
A more interactive approach could help reinforce topics better, with more challenges and immediate practice opportunities throughout the course.
Additional care should be taken in setting up resources, as some students faced difficulties in finding or accessing appropriate data files.