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.
Introduction to PySpark
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3.6
(18 reviews)
Beginner level
Recommended experience
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Data processing with Pyspark
Skills you'll gain
Details to know
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Assessments
5 assignments
Taught in English
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There is 1 module in this course
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.
What's included
27 videos7 readings5 assignments2 discussion prompts
Recommended if you're interested in Software Development
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Frequently asked questions
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.
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.
The course lasts approximately three hours and covers topics such as Big Data, Hadoop, Spark architecture, and PySpark.