Jamie Allen
Biography of instructor/staff member #1
Offered By: Big Data University
Spark Overview for Scala Analytics
The “Spark Overview for Scala Analytics” course will cover the history of Spark and how it came to be, how to build applications with Spark, establish an understanding of RDDs and DataFrames, and other advanced Spark topics. Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Having finished this class, a student would be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets. This course is meant to be an overview of Spark and its associated ecosystem. For deeper understanding of Spark, we recommend that students take the Spark Fundamentals courses I and II.
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11k+ EnrolledAt a Glance
The “Spark Overview for Scala Analytics” course will cover the history of Spark and how it came to be, how to build applications with Spark, establish an understanding of RDDs and DataFrames, and other advanced Spark topics. Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Having finished this class, a student would be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets. This course is meant to be an overview of Spark and its associated ecosystem. For deeper understanding of Spark, we recommend that students take the Spark Fundamentals courses I and II.
About This Course
The “Spark Overview for Scala Analytics” course will cover the history of Spark and how it came to be, how to build applications with Spark, establish an understanding of RDDs and DataFrames, and other advanced Spark topics. Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. Having finished this class, a student would be prepared to leverage the core RDD and DataFrame APIs to perform analytics on datasets.
This course is meant to be an overview of Spark and its associated ecosystem. For deeper understanding of Spark, we recommend that students take the Spark Fundamentals courses I and II.
There are 5 modules to this course.
1. What is Spark
2. Introduction to RDDs
3. Introduction to DataFrames
4. Advanced Spark Topics
5. Introduction to Spark MLlib
Requirements
1.Taken the Introduction to Scala Course
2. Experience with Java (preferred), Python, or another object oriented language
3. No previous Spark knowledge is required
4. No previous experience with Data Science concepts is required. These concepts will be explained as needed
Course Staff
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Estimated Effort
08:00
Course Code
SC0103EN