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Online Course

Big Data Analytics Using Spark

University of California, San Diego via edX

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  • Provider edX
  • Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Effort 9-12 hours a week
  • Duration 10 weeks long
  • Learn more about MOOCs

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Overview

In data science, data is called "big" if it cannot fit into the memory of a single standard laptop or workstation.

The analysis of big datasets requires using a cluster of tens, hundreds or thousands of computers. Effectively using such clusters requires the use of distributed files systems, such as the Hadoop Distributed File System (HDFS) and corresponding computational models, such as Hadoop, MapReduce and Spark.

In this course, part of the Data Science MicroMasters program, you will learn what the bottlenecks are in massive parallel computation and how to use spark to minimize these bottlenecks.

You will learn how to perform supervised an unsupervised machine learning on massive datasets using the Machine Learning Library (MLlib).

In this course, as in the other ones in this MicroMasters program, you will gain hands-on experience using PySpark within the Jupyter notebooks environment.

Taught by

Yoav Freund

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