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

4.7
2,011 ratings
406 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

CC

Jun 08, 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!

CR

Apr 10, 2017

Great introduction to spark. Fun assignments. Since it was the first ever session, there were quite a few kinks with the assignments. But the discussion forums rescued me any time I was stuck.

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376 - 390 of 390 Reviews for Big Data Analysis with Scala and Spark

By Luis V

Oct 01, 2017

Good course but with many outdated concepts (mostly valid for Spark 1.x) and some pitfalls. Need many improvements, actualization and some reshaping in the distribution of the topics and sessions of the course. The topics left for the last week are some of the most important and central in current Spark 2.x and they include at least as many fundamental concepts as the rest of the course.

By Harold O

Apr 16, 2017

This is a really excellent course. It deals with difficult content clearly, thoroughly and at a good pace. I would now be happy to use Spark in my work and feel I have a strong base to go on to further study. The exercises are well conceived covering fairly realistic use cases and are of about the right complexity. BUT, the feedback from the automatic grading really lets it down.

The auto grading tests are at too high a granularity, each test tests too many things. They give cryptic errors such as '<some random element> is empty'. You have no idea why the element is empty as the students are given a different dataset to the one tested on. Moreover, the failed tests are invariably nothing to do with learnt course content, but trivial rounding/formatting errors. The forums are a lifesaver, but I still spent a good two weekends working on bugs once I'd got the assignments 70% right. I would not recommend to a completist!

All the same, thanks to Heather for the wonderful work she's done putting it together and the excellent lectures she gives.

By Sam Z

May 03, 2017

good: the concepts and on-hands skills taught by the course are good.

bad: the assignments. you cannot complete them just by following the course material, forcing you to waste quite a lot of time either: (1) learning from other sources; (2) looking for answers on the forum; or (3) brute forcing an answer till rage quitting :)

another bad point: the course is supposed to be focused on spark & big data analysis but it has 1-2 lectures (around 40-60 mins) pretty much devoted to showing some SQL. << this could be summarized to around 10-20 mins and/or give a link to quickly learn/try to some other source.

By Rafael G

Mar 31, 2017

The material in this course is very interesting. However, there were a few important issues:

Lots of typos in the slides

Lots of problems with the assignments

At the end, I feel like a beta-tester (it would be OK if it was clearly stated and if we had a discount).

It could also be nice to add 1 or 2 weeks to this course.

By Yann L M

Mar 19, 2017

Lectures are great. Explanation are very clear. Assignment was having issue like incorrect and/or vague reporting which made them needlessly painfull. I'm quite sure that the next iteration of this course can get a 5 star rating, but for now, it's only 3.

By Alexandre V

Nov 25, 2017

Explanations are OK and it's a good investment. However, I'm mixed about the courses: the teacher is speaking really fast with slides full of text. It's sometime hard to keep my concentration (compared to previous courses of the specialization). Still, I would recommend this course.

By Lance F

Mar 27, 2017

This course took a lot of work to create. I would have like more quizzes during the lectures and the assignments to have walk through the steps more. The best course I have seen online is the Machine learning course by Andrew Ng. https://www.coursera.org/learn/machine-learning/home/welcome.

I did really enjoy the course. Thank you.

By Kyle J

May 22, 2019

Pretty good, but one of the assignments was poorly set up. Some of the provided code was broken and it was very hard to debug.

By Owen N

Apr 09, 2017

Course material was pretty good, but the lectures were hard to watch. Lots of editing problems, and blurring on the text (gave me a headache several times). Would rate higher if the videos were improved.

By Mikołaj J

Jun 05, 2017

So many mistakes in the slides. Coding exercises are so hard to comprehend, it's tough to know what you are trying to achieve. I have already done a course in spark, this was supposed to be just refresher, but now I'm just confused...

By José F

Apr 18, 2017

a let down and not up to par with other courses in the series.

Huge amount of time is wasted bsically repeating that the API is close to scala collections'. The huge amout of time is wasted again on very simple dataframe APIs including several slides presenting the show() function. Allow me to repeat : several slides presenting the show() function.

Finally the assignments are unimaginative and mechanical. The desciption is really confuse and most of the time is spend trying to chase small differences away to please the grader.

The sole part of the course that seemed interesting was the shuffling one, that was unfourtunately ignored on the assignments

Not related to the course but to spark: What utter mess are dataframes and datasets filled with boilerplate type conversions and runtime erros. I shy away in disgust form this untyped IDE-unfriendly monstruosity.

By Vladyslav S

May 06, 2017

Relatively decent video lectures, if not that blurry which makes text hard to read. Accompanied with awful practice lessons: - code templates are written with little to no style, even file reading is done in 3 different ways in all 3 lessons; - grader output is very confusing and almost useless; - unit tests, very useful to avoid some common caveats, were present in the first lesson, disappear completely in the last one.

Probably following spark's programming guide is better time investment, even if it misses some "humanity" of video lectures

By Марко И

Apr 10, 2017

I don't know what happened but it seems they had technical or some other problem while preparing this course. Some assignments were more oriented to solving marginal problems then using Spark and distributed and parallel computing. And that is really annoying. Previous 3 courses were great, maybe this one will improve.

By Dan O

Mar 25, 2017

Slow videos repeating several times the same thing (not a pedagogical / "good to fix an idea" kind of repetition), which makes them hard to follow.

However the worst are the exercises: the first time after 3-4 other Coursera Scala related courses where I have to actively check the forums for minute details about what is expected / implied for the solutions to pass the grading.

Things like what to do when updating the kmeans and you have duplicates, subtle differences between average and mean, etc. ...

In all other courses the expectation of the exercises were sufficiently clear and straight forward that I never had to check the forums to solve them.

Also, the code style of the exercises is literally an anti-pattern in idiomatic Scala, against everything learnt in the previous Scala courses: "var" all over the place, low level loops like in C or Java, etc. ...

By Bulat S

May 19, 2018

The course is too basic.