On which platforms PySpark is being used?

<text variant="body1">PySpark is used on various platforms, including cloud services like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), as well as on-premises clusters and local machines, providing flexibility for distributed data processing across different environments.

Is PySpark free to use?

<text variant="body1">Yes, PySpark is an open-source distributed computing framework that is freely available. It allows users to process large-scale data sets efficiently using Python APIs on Apache Spark's distributed processing engine.

What is the duration of the course?

<text variant="body1">The course lasts approximately three hours and covers topics such as Big Data, Hadoop, Spark architecture, and PySpark.

What will l learn from this course?

<text variant="body1">Throughout this course, you will be able to familiarize yourself with topics such as Big Data, Working with Hadoop, working with Spark, Spark architecture, and Data processing implementation with PySpark.

What are the prerequisites for this course?

<text variant="body1">This is an introductory course designed for absolute beginners. While prior knowledge of Python is advantageous, participation is not mandatory.

What is this course about?

<text variant="body1">This course offers comprehensive insights into Data Processing with PySpark. This course is designed to empower learners with the knowledge and skills needed to get started with Data processing with PySpark.

Who is this course designed for?

<text variant="body1">This course caters to a diverse audience, embracing those new to the field as Freshers. Data Analysts and Data Scientists will enhance their skills in Big data Processing, while Data Engineers will gain insights into seamless Spark architecture and data processing with PySpark.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Introduction to PySpark

Instructor: Edureka

7,119 already enrolled

Included with

Learn more

1 module

Gain insight into a topic and learn the fundamentals.

51 reviews

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

51 reviews

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand PySpark fundamentals to process big data efficiently using Python APIs.
Apply real-time data processing techniques for actionable insights.
Explore Spark architecture for distributed computing and scalability.
Build hands-on skills with PySpark through practical assignments.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

There is 1 module in this course

Welcome to Introduction to PySpark, a short course strategically crafted to empower you with the skills needed to assess the concepts of Big Data Management and efficiently perform data analysis using PySpark. Throughout this short course, you will acquire the expertise to perform data processing with PySpark, enabling you to efficiently handle large-scale datasets, conduct advanced analytics, and derive valuable insights from diverse data sources.

During this short course, you will explore the industry-specific applications of PySpark. By the end of this course, you will be able to: 1. Attain a basic understanding of the introduction of big data, including its characteristics, challenges, and importance in modern data-driven environments. 2. Familiarize with Spark architecture and its components, such as Spark Core and Spark SQL. 3. Familiarize with distributed computing concepts and how they apply to Spark's parallel processing model. 4. Explore PySpark and big data concepts to solve data-related challenges. 5. Write PySpark code to solve real-world data analysis and processing tasks. This short course is designed for Data Analysts, Data Engineers, Data Scientists, and Big Data Developers seeking to enhance their skills in utilizing PySpark for data processing and analysis. Prior experience with Python and Hadoop is beneficial but not mandatory for this course. Join us on this journey to enhance your PySpark skills and elevate your analytical and design capabilities.

Module details

Welcome to Introduction to PySpark. In this short course, you will learn the fundamental concepts of PySpark and Bigdata, and learn to perform real-time data processing with PySpark to gain useful insights from the data.