PySpark in Action: Hands-on Data Processing is a foundational course designed to help you begin working with PySpark and distributed data processing. You will explore the essential concepts of Big Data, Hadoop, and Apache Spark, and gain practical experience using PySpark to process and analyze large datasets. Through hands-on exercises, you will work with RDDs, DataFrames, and SQL queries in PySpark, giving you the skills to manage data at scale.
PySpark in Action: Hands-On Data Processing
PySpark in Action: Hands-On Data Processing
This course is part of PySpark for Data Science Specialization
Instructor: Edureka
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
15 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Explore the fundamental concepts of Big Data and the components of the Hadoop ecosystem.
Explain the architecture and key principles of Apache Spark and its role in big data processing.
Utilize RDD transformations and actions to effectively process large-scale datasets with PySpark.
Execute advanced DataFrame operations, including data manipulation and aggregation techniques.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
October 2024
Assessments
17 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the PySpark for Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 5 modules in this course
This module introduces you to the fundamental concepts of Big Data and Hadoop. You will explore the Hadoop ecosystem, its components, and the Hadoop Distributed File System (HDFS), setting the foundation for understanding big data processing and storage solutions.
What's included
15 videos5 readings4 assignments1 discussion prompt
Dive into the core of PySpark by learning about Resilient Distributed Datasets (RDDs). This module covers the fundamentals of RDDs, how they work, and their key transformations and actions, enabling efficient distributed data processing in PySpark.
What's included
25 videos4 readings4 assignments3 discussion prompts
This module covers the creation and manipulation of DataFrames in PySpark. You will learn how to perform basic and advanced operations, including aggregation, grouping, and handling missing data, with a focus on optimizing large-scale data processing tasks.
What's included
22 videos4 readings4 assignments1 discussion prompt
In this module, you will explore the SQL capabilities of PySpark. Learn how to perform CRUD operations, execute SQL commands, and merge and aggregate data using PySpark SQL. You'll also discover best practices for using SQL with PySpark to enhance data workflows.
What's included
28 videos4 readings4 assignments2 discussion prompts
This module is meant to test how well you understand the different ideas and lessons you've learned in this course. You will undertake a project based on these PySpark concepts and complete a comprehensive quiz that will assess your confidence and proficiency in Data Processing with PySpark.
What's included
1 video1 reading1 assignment1 discussion prompt
Recommended if you're interested in Data Analysis
Coursera Project Network
Coursera Project Network
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
You will need access to a computer with Python and Apache Spark installed. Detailed setup instructions will be provided at the beginning of the course.
This course is designed for individuals new to big data and PySpark, providing a solid foundation to start working with distributed data processing.
While prior SQL knowledge is beneficial, it is not mandatory. The course will introduce SQL concepts as they relate to PySpark and provide practice with SQL queries.