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Tackling the Problem of Big Data Hands-On: Distributed Computing with Spark (NEW)

Duration: Three Day Course

Prerequisite: Basic to intermediate Python, basic to intermediate programming, and/or successful completion of the Introduction to Machine Learning course

Spark is at the forefront of distributed computing. This module is taught using Python and includes the basics of critical functional programming constructs such as map, flatmap, list comprehensions, and data structures.

We cover core concepts of Spark-like resilient distributed datasets, memory caching, actions, transformations, tuning, and optimization. Students get to build functioning applications from end to end and learn critical tooling to enhance productivity. They apply that knowledge directly to developing, building, and deploying Spark jobs that they will run on large, real-world datasets in the cloud (AWS and Google Cloud Platform).

You Will Learn

  • Basics of the Spark API
  • Big data development considerations and techniques

Geared To

  • Data analysts or data scientists with some programming experience looking to utilize advances in cloud computing to more effectively work with big data

Technology Requirements

  • All attendees must have a laptop with Google Chrome installed
  • Classroom must be equipped with WiFi and an HDMI enabled projector

Contact Us to Get Started Today


Yvonne Baho

Yvonne M. Baho Director, Enterprise Learning
Phone: 978.582.7105
E-mail: ybaho@tdwi.org


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