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.
Learn Apache Spark and Scala for enterprise-level big data processing. Master RDDs, SparkSQL, and real-time analytics using Spark MLlib.
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.
Instructors:
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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
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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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
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Instructor
Enhancing IT Education Through Expert-Led Learning
Packt Course Instructors are dedicated to delivering high-quality educational content across a wide range of IT topics, offering over 5,000 eBooks and courses designed to improve student outcomes in technology-related fields. With a focus on practical knowledge, instructors leverage their industry expertise to create engaging learning experiences that help students grasp complex concepts and apply them effectively. The courses cover diverse subjects, from programming languages to advanced data analysis, ensuring that learners at all levels can find relevant resources to enhance their skills. Additionally, Packt emphasizes personalized learning paths and provides analytics tools for educators to monitor student engagement and success, making it a valuable partner in academic settings.
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