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Отзывы учащихся о курсе Big Data Analysis with Scala and Spark от партнера Федеральная политехническая школа Лозанны

4.7
звезд
Оценки: 2,548

О курсе

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....

Лучшие рецензии

BP

28 нояб. 2019 г.

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

7 июня 2017 г.

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!

Фильтр по:

476–500 из 506 отзывов о курсе Big Data Analysis with Scala and Spark

автор: Rug

10 мар. 2022 г.

The course contents were good, but some warm up exercises which are easier would have been great. Further, the grading scheme ist not that transparent and in particular in the last assessemet some sample unit tests would have been helpful.

автор: Benjamin S

12 сент. 2017 г.

The lectures are really great with vivid and easy-to-follow explanations on complex topics.

However, the exercises don't seem to match the lectures very well and may confuse you. I would prefer to apply the things I learned in the lectures.

автор: Gian U L

7 мая 2017 г.

In the assignments, I had the feeling that the goal was more "guess what they want" than "write it correctly using what you have learnt". Stating more clearly the requirements and improving error messages from the grader may help.

автор: Aaron H

22 янв. 2018 г.

Instructor was good and knew what she was talking about. The assignments were also good, but the grading was weird. Spent a lot of time try to figure out the unwritten requirements that would make Coursera's tests pass.

автор: Virapat K

2 февр. 2021 г.

The course is good overall. The assignment is OK. The tests should and grading should be more transparent. There are a lot of errors that are difficult to decipher.

Also week 2 assignments have bugs in the codes.

автор: Serg D

14 апр. 2020 г.

It was a good course, much more useful than the first one in the series. I would say too much focus was on the SQL side and not enough on the big data side, which is what i was hope to get from the course.

автор: Aitor S G

24 февр. 2021 г.

The course is okay, but the presentations are blurry, which is annoying. I would like to go more in-depth, like optimizations, stages, partition pruning...

автор: Nikita V

11 мая 2017 г.

I guess it's a goo introduction course into Apache Spark. Meantime I would expect deeper dive into optimizations and algorithms.

автор: Moiseenko A

6 мая 2020 г.

There is not any course support at all.

Provided drafts of program assignments does not satisfy SOLID and Clean-code principles

автор: Kyle J

21 мая 2019 г.

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.

автор: Virginija D

7 авг. 2017 г.

Too entry-level after the first two much more challenging courses by M. Odersky.

автор: Jinyi S

9 мая 2021 г.

It's a little bit difficult for me in its configuration part

автор: Hans R

25 окт. 2020 г.

Explains the core concepts very well, but lacks depth.

автор: Mortatha K H

8 июля 2020 г.

it's hard for beginner understanding this course

автор: Ioannis A

25 сент. 2018 г.

course needs to be updated

автор: Cherniaev A

7 февр. 2021 г.

Good, but outdated course

автор: José F

17 апр. 2017 г.

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.

автор: Vladyslav S

6 мая 2017 г.

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

автор: Prathviraj S C

25 февр. 2020 г.

How to execute assignments and weekly work is not properly described in assignment task, it took lot's of time to understand how to execute the project and which software with what configuration is needed. This course is good to learn but submitting assignments is very much difficult. This course can become awesome if the proper guidance is provided for submitting tasks and if demo available how to execute the same.

автор: Mikołaj J

5 июня 2017 г.

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...

автор: Owen N

9 апр. 2017 г.

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.

автор: Vassileios L

5 июня 2021 г.

There is no Scala taught whatsoever, the title is misleading. I had to use stackoverflow in hardcore mode to be able to solve the assignments and the lessons did not help almost at all with that.

автор: rafael f o

7 июня 2020 г.

not good teacher lessons

автор: Dan O

25 мар. 2017 г.

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. ...

автор: Марко И

10 апр. 2017 г.

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.