Course is good to have some practice in spark and scala. However it seems to be long forsaken by staff and some issues with assignments require doing archaeology in the forums. Also it is quite unpleasant to see that while specialization emphasizes functional programming, some auxiliary code in assignments is written in the worst manner of imperative programming... Why use scala then?

If you know the subject, may be easy. If you don't know the subject, too dense and abstract with not enough practical examples/exercises before the assignments (specially for week4). Would have been better to break the videos into smaller ones, include more practical concrete examples/exercises during the videos (as very well done by Pr. Obersky during the 1st Course of the Specialization). There could have been room to break week4 into material for 2 weeks. Still, inresting.

Very Nice and effective course. One of the best course i have done on Spark online. Many Thanks to the course instructor Heather Miller for creating a very detail and updated course on Spark.

A superb course taught by a superb lecturer. From a lecture stanpoint, my only recommendation is that additional lectures be provided to flesh out the coverage of Datasets. I found the assignments challenging and a good reflection on my understanding of the course material. I would recommend only the following tweaks:

Week 1 assignment: Either tightly specify the function that determines if a particular String is present in a large textstring OR provide the function in the assignment skeleton. There are too many ways to approach this function that are correct, but different than the one the grader used. This function is only incidental to the goal of applying one's knowledge of Spark to the assignment.

Week 4: Allocate additional lectures to flesh out the coverage of Datasets. The subject was not covered to the same level of detail that the other subjects in the course were given.

These are minor points.

Well done, Dr Heather Miller!

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.

Very interesting course. Heather presents at just right level of abstraction to my taste and her presentation is very lively so it is easy to stay focused.

Formally, this is a course on a particular set of software tools and many such courses are not very useful unless one is to start applying learned skills immdeiately because the material starts getting obsolete the day the course is passed.

I believe that this course, however, teaches important priniples that outlive the particular toolkit, in particular the art of reasoning about algorithms on distributed collections, in particular, their performance. One would expect this to be a complex subject but somehow this course makes it feel simple -- which is a good indicator of high quality.

It's a great course with lots of insight into spark. At first it's confusing - first rdds; then dataframes and later datasets. But this is by no means the instructors' fault. Heather greatly describes in detail what goes on under the hood and why dataframes are way faster than simple rdds and why we have to give up some of our beloved typesafety of scala-land to let catalyst do its magic. Datasets try to bring some of it back.

I really enjoyed coding the assignments. Took me ~2hrs each. The tasks were fun and like those you would find in the wild.

I already applied some of the skills I learned here at work and successfully implemented a simple recommendation engine that will go to production next week.

Highly recommend this course!

Course is solid, useful concepts are thought. Assignments are interesting.

Points for improvement:

I wish this course was 2-3 courses focusing on topic with more assignments. If a concept is reviewed by the student is not challenged with tough questions the concept is not learned. People taking this course are already advanced enough to tackle difficult challenges, sometimes it appears that instructor assumes that students are entry level.

A note for online instructors: avoid jokes. They do not work online.

I think a specialization on applications of spark with scala covering AI, graph and text processing would be interesting. Overall thanks for the effort; pretty good.

I learned so much from this course! It was amazing how Dr. Miller used concepts that were meticulously built up in the earlier courses, such as evaluation strategy, functional collections, reactive programming, and associativity, to describe the core of Spark in only four units. As someone coming from more of a statistics background, I started this specialization only to learn Spark, so I wasn't always sure how relevant learning the more theoretical underpinnings of Scala would be. It turns out that it was pretty essential, while also just making me a better programmer. Looking forward to the capstone!

Great course over Spark. It shows the syntax, but more than this, it shows the problems, the caveats, the optimization and the architecture from a wide point of view.

The assignment were designed to focus right to the point: they managed all the configuration and initialization code of the project, leaving the student to fill only the most important part, with the resulto of having, at the end of the course, working projects that could be used as "cheat sheet" to remember all the material of the course.

Massimiliano.

I like the course. Very interesting and stimulating. Week 4 is a bit cumbersome, but it is due to a big amount of topics covered in it. I think that it could be better to have a DataSets and DataFrames brief overview in this course and study these topics in detail in separate advanced courses.

Assignments are designed to make us spend some time reading the docs. I think that it is good, as by doing so I have learned a bit more.

Many thanks to Prof. Heather Miller!

Very nicely taught. Liked these "long" lectures of 15-20 min where the instructor gradually builds the material around the topic. Most other courses online, especially Udacity has frustratingly short videos where more than half the time the student has to keep clicking to the next video. Material coverage is sufficiently wide as well and the curriculum is freshly designed which is very important in this field.

The course presented the concepts in a clear and exemplified way. Tough, it was a bit too verbose.

The exercises were not too hard and thorough enough to cover the concepts presented in class.

I wished there were more exercises as Spark's API is huge and sometimes a bit tedious to use thus being hard to quickly get confident. I hope that the capstone project will help for that.

The course covers the important concepts and explains them in detail.

Homework tasks really make you think, revisit the lectures and read documentation, until you get it right, and that all deepens understanding of the material.

I also obtained some clues for the future: the lectures provided me with context, which helps formulate questions when searching for answers elsewhere.

This is a great course on the intricacies of Apache Spark. It is not a general Big Data course, neither is it an easy one. Doing the programming assignments properly requires reading a lot trough the Spark documentation, which I personally liked as part of the challenge, but beware if you are not that type of person or aim at finishing the course as quickly as possible.

Excellent course. I had some knowledge about Spark before but this course helped me to leverage my skills from pure theory to something practical. Now I have the confidence I can use spark to solve real life problems. This specialization as a whole is totally changing my career prospect. Thank you EPFL, Dr. Miller and Coursera for providing such opportunity for me.

Greate course to get an overview of Spark. Heather's teaching style is awesome. Her style really helps to connect the dots. Explains a lot on 'why' along with 'how'. To get full benefit, do as a continuation of other scala courses in the specialization. It would have been nice if there was a gentle intro to other areas like ML and Streaming. Great course.

I really enjoyed this course! First of all I would like to congratulate the people behind this effort. The videos are clear, to the point and they contain very useful information and tips that are very difficult to get from a book. I hope that you will continue with a second course on Spark and Scala with more advanced topics. Thank you very much.

The course gave me insight into the world och big data batch processing and how Spark solves it. Heather does a great job with presenting the material in a thorough way with relevant theory and illustrative examples. The assignments are well balanced and forces you to apply all your new knowledge when solving them. I highly recommend this course!

An introductory course to spark programming, lectures are well-balanced between theory and boier-plate codes, but programming assignments are mainly about teaching you the APIs. The problem-solving part is basically trivial, whereas most of the time were spent on searching for API documents and correcting compiler errors and runtime exceptions.

This is my first cource review on English, but I want to do accent on Heather's high professionalism, great explanations abilities and great organisation of material. I need to say that I have education of computer science teacher and I can say that it's wonderful cource. It was difficult for me and I've really increased my skill. Thanx.

As always, Coursera delivered another top quality courses on Spark with Scala. I have learned a lot of details, understood the underlying working principles of Spark in the last few days. Thanks to Dr. Miller for such a great course. I hope in the future versions of this course the overall presentations will be more smooth and typo-free.

this course help me form a basic understanding of Spark and how to use it to analyze large scale dataset. Besides fundamental knowledge of how to use, the lecturer also provide students with some deeper concept of how to optimize the performance of spark programming, which can be very useful in running code on large dataset.

Thank you Dr. Heather Miller and the EPFL team along with coursera team for this course. I found it interesting. It gave me complete insight of spark. I had a great start with spark.

The internal working of spark API, the shuffle operations, query optimization and many more tips are really useful. Thank you once again.

This course is a great introduction to Spark. The only thing I think could be improved is that each programming assignments has unit tests that drive students towards the final solution. I saw lots of people complaining in the forums about this slow and tedious back and forth of having the grader testing their code.