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Mastering Big Data with Apache Spark and Scala
Learn Apache Spark and Scala for enterprise-level big data processing. Master RDDs, SparkSQL, and real-time analytics using Spark MLlib.
Course Cost
Free course
Intermediate
Skill Level
10 Hours
Self-paced lessons
This comprehensive course provides hands-on training in Apache Spark and Scala for big data processing. Starting with a Scala crash course, students learn to work with Spark's core concepts like RDDs and advanced features including SparkSQL, DataFrames, and DataSets. The program covers practical applications in machine learning with MLlib, real-time analytics using Spark Streaming, and graph processing with GraphX. Through hands-on exercises, students gain experience in cluster deployment, performance optimization, and implementing real-world big data solutions. The course is designed for software engineers looking to expand their expertise into distributed data processing.
English
What you'll learn
Design and implement advanced Spark applications for complex data processing
Develop and execute efficient Spark scripts for large datasets
Master RDDs, DataFrames, and DataSets for data manipulation
Implement machine learning solutions using Spark MLlib
Create real-time data processing pipelines with Spark Streaming
Optimize Spark applications for cluster deployment
Build graph-based analytics using GraphX
Skills you'll gain
This course includes:
535 Minutes PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 10 modules in this course
This comprehensive Apache Spark and Scala course offers deep training in big data processing techniques. The curriculum progresses from fundamental Spark concepts through advanced topics including RDDs, SparkSQL, machine learning with MLlib, and real-time processing with Spark Streaming. Students learn through hands-on exercises, working with real-world datasets and implementing practical solutions. The course covers cluster deployment, performance optimization, and integration with cloud services, preparing learners for enterprise-level big data challenges.
Getting Started
Module 1 · 40 Minutes to complete
Scala Crash Course (Optional)
Module 2 · 1 Hours to complete
Using Resilient Distributed Datasets (RDDs)
Module 3 · 1 Hours to complete
SparkSQL, DataFrames, and DataSets
Module 4 · 1 Hours to complete
Advanced Examples of Spark Programs
Module 5 · 1 Hours to complete
Running Spark on a Cluster
Module 6 · 1 Hours to complete
Machine Learning with Spark ML
Module 7 · 48 Minutes to complete
Introduction to Spark Streaming
Module 8 · 41 Minutes to complete
Introduction to GraphX
Module 9 · 33 Minutes to complete
You Made It! Where to Go from Here
Module 10 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
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