听

  • Specialization:听Software Architecture for Big Data
  • Instructor:听Tyson Gern and Mike Barinek
  • Prior knowledge needed:听Software engineering or big data experience

Learning Outcomes听

  • Compare, measure, and test big data models for production use.
  • Write听 custom performance tests to measure the characteristics of a distributed system.
  • Use queues to horizontally distribute large workloads
  • Describe pessimistic and optimistic concurrency, and identify when each can be used to solve performance issues.

Course Content

In this module, you will learn how to write tests that allow you to iterate on predictive models.

In this module, you will learn how to write performance tests to ensure your distributed system operates as expected in production.

In this module, you will learn how to use queues to horizontally distribute large workloads.

In this module, you will learn the advantages and disadvantages of high availability distributed systems.

Duration: 1hr

You will complete a peer reviewed final project worth 30% of your grade. You must attempt the final in order to earn a grade in the course.听If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.

Note: This page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click听View on Coursera听button听above for the most up-to-date information.