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Learner Reviews & Feedback for Big Data Analysis with Scala and Spark by École Polytechnique Fédérale de Lausanne

4.7
stars
2,385 ratings
•
494 reviews

About the Course

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance. Learning Outcomes. By the end of this course you will be able to: - read data from persistent storage and load it into Apache Spark, - manipulate data with Spark and Scala, - express algorithms for data analysis in a functional style, - recognize how to avoid shuffles and recomputation in Spark, Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming: https://www.coursera.org/learn/parprog1....

Top reviews

BP
Nov 28, 2019

Excellent overview of Spark, including exercises that solidify what you learn during the lectures. The development environment setup tutorials were also very helpful, as I had not yet worked with sbt.

CC
Jun 7, 2017

The sessions where clearly explained and focused. Some of the exercises contained slightly confusing hints and information, but I'm sure those mistakes will be ironed out in future iterations. Thanks!

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226 - 250 of 477 Reviews for Big Data Analysis with Scala and Spark

By Dmitriy K

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Mar 20, 2017

Thanks Heather! You did a great job with this course.

By Robson R S P

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Apr 12, 2020

If you are a spark beginner, this is a great course.

By Alexey A

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Jul 13, 2019

The most interesting course in whole specialization.

By 李东恒

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Jan 24, 2020

Very good course for learning and practicing Spark.

By Yuri R

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Oct 24, 2019

Liked the course. Wasn't familiar with spark before

By Cliff R

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Jul 22, 2018

Gives a good grounding in the fundamentals of Spark

By Kovalenko S

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Jul 17, 2017

Курс очень понравился, спасибо большое за ваш труд!

By Adrien C

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Jun 29, 2017

Interesting course, the last week feels most useful

By Juan L R A

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Jun 19, 2017

Very good course and good materials for learning

By Florian B

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Nov 18, 2017

Super cours, merci beaucoup! EPFL always rocks.

By Devaki B

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Apr 15, 2017

It was good. Got indepth knowledge of Spark API

By Harshad H

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Oct 30, 2019

Best Course for Big Data Learning in the World

By David F S

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Jan 14, 2019

Very informative. Well-organized presentation.

By Husain K

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May 7, 2017

Great course, learnt a lot from it. Thank you.

By samy k

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Mar 21, 2017

Interesting and challenging course! Thank You!

By Robert C M P

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Feb 11, 2019

Excellent videos, explanation, and resources!

By shubham m

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Jul 10, 2018

good but give more practical of small program

By abdhesh

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Dec 31, 2017

It was an awesome and well explained course.

By Jeroen M

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Apr 9, 2017

Great course, well explained, instant value!

By Hong C

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Apr 14, 2020

A perfect resource to get start with Spark.

By Denys L

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Dec 5, 2018

Very nice, but a little bit outdated course

By Zhenhua w

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Oct 30, 2019

The lecture is well-organized

and excellent

By Muhammad B

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Jun 10, 2020

Very brilliant instructor, learned a lot.

By Arnaud J

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Jun 2, 2017

Great course. Would definitely recommend.

By Daniel D

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Apr 20, 2017

Great course - well prepared by the team.

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