• Length:
    10 Weeks
  • Effort:
    9–12 hours per week
  • Price:

    FREE
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  • Institution
  • Subject:
  • Level:
    Advanced
  • Language:
    English
  • Video Transcript:
    English

Associated Programs:

Prerequisites

  1. The previous courses in the MicroMasters program: DSE200xDSE210x and DSE220x

About this course

Skip About this course

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.

What you'll learn

Skip What you'll learn
  • Programming Spark using Pyspark
  • Identifying the computational tradeoffs in a Spark application
  • Performing data loading and cleaning using Spark and Parquet
  • Modeling data through statistical and machine learning methods

Meet your instructors

Yoav Freund
Professor of Computer Science and Engineering
UC San Diego

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Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.