Big Data Analysis with Scala and Spark

Course Feature
  • Cost
    Free
  • Provider
    Coursera
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    No Information
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Functional Programming in Scala Specialization
Next Course
4.6
96,924 Ratings
Unleash the power of big data with "Big Data Analysis with Scala and Spark" course. Discover how functional concepts revolutionize data manipulation in industry. Dive into Apache Spark, the cutting-edge distributed collections framework, and explore its programming model. From reading and loading data to advanced manipulation and algorithm design, master the art of data analysis in a functional style. Learn to optimize performance by addressing distribution challenges like latency and network communication. Gain invaluable skills to read, manipulate, and analyze data at scale. Recommended for programmers with experience in languages like Java, C#, or Python. Take your data analysis to the next level and enroll today.
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Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 14th, 2023]

This course explores the manipulation of large-scale data distributed over clusters using functional concepts, which have become integral to various industries. We delve into Apache Spark, a fast, in-memory distributed collections framework written in Scala, that extends the data parallel paradigm to the distributed case. Through hands-on examples in Spark and Scala, participants will learn how to effectively address issues related to distribution, such as latency and network communication, to optimize performance. By the end of the course, learners will be able to read data, manipulate it using Spark and Scala, express data analysis algorithms in a functional style, and avoid unnecessary shuffles and recomputation in Spark. It is recommended to have at least one year of programming experience, with proficiency in Java or C# being ideal. Familiarity with other languages such as C/C++, Python, Javascript, or Ruby is also sufficient. Join now and expand your skills in big data analysis with Scala and Spark.

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