For now, the worst course in Specialization.

This course was okay, but I feel it could use some work. For starters:

-I feel some of the longer assignments should be split up into several weeks (the Barnes-Hut one for example, since there's a lot to implement and it took a while to understand conceptually).

-I feel that some parts of the assignment specs could be more clear. For example, in the K-means assignment, it was mentioned to use the "square distance" between the means to determine if the algorithm had converged or not and I feel it would be useful to provide a mathematical formula here (or at least give the name of the formula i.e., Pythagorean).

-I wish there was more focus on making the assignments practical instead of something that's more sophisticated. For example, it would've been nice to have an assignment for week 4 that allowed us to practice implementing a variety of parallelizable data structures and focus on making them as efficient as possible.

Good course. But I have a strong feeling that would be nice to have more focus on the practice. Some lecture not really much with the results of assignments. Good course anyway. Pavel

Content is good, less well polished than Odersky's courses though. Painful exercises with a lot of time spent on understanding the instructions instead of focusing on learning parallelism methods (especially the final assignment). Overall happy to have learnt from this, but clarity of assignments should be improved.

In my view, this course was nowhere near as good as the earlier courses by Prof Odersky. The materials and pacing seemed all over the place - in some cases excessive time was spent going through quite trivial concepts, while elsewhere the course seemed quite rushed when looking at much more complicated ideas.

Most of assignments are good. They show applications of parallel programming very well. Some lectures are booring? but important. For instance, lectures about assotiativity.

Not friendly with beginners in Scala. You will be presented with tons of Scala code with minimal detailing on algorithms. Obviously the lecture expects you to be quite familiar with Java and Scala. And the lecture is not very informative either (at least for green hands in Scala). I found that the best way that works for me is to pause at each slide, study the code, and then go on to see what the lecture has to say.

should contain more details

Good learning materials, however the assignments are designed for compute science students rather than professional software developers as the most important part of the assignments is not parallel code, but it is algorithms. Yes, there is parallel code in the code of the assignments, but it is mostly written and your task is to implement the algorithm using this existing parallel code, while in my opinion it should be the other way around - you should implement parallel code and algorithms code should be already provided for you.

I didn't like the last assignment. I didn't think there was much to learn there. I would've liked to implement more splitters and combiners. I did like the first 3 assignments very much. The lectures were pretty good, but I found myself loving some, and hating the others. I would've preferred more practical applications over theory. I think the lectures are un-necessarily math heavy.

Deep lectures, but exercises where more about complex problems than about parallel programing

Not enough Scala. Akka version was better :(

Online video is OK. But assignments are not much related to parallel programming specific issues. One case, this is my opinion but it's nice if students learn how scala solves "The dining philosophers" issue.

This course could have been better in my opinion, if we could have exercise that would deal with the concepts in more detail. I felt myself involved deeply in understanding the problem statement, rather than practicing the concepts explained in the course.

Good but too theoretical and not very didactic.

Good content. Very basic overview of parallel programming algorithms and data structures in scala. Course feel a little bit hacked together although not as bad as the Functional Program Design one.

Course should be more in depth.

There are not clear test errors, that points to another place in code where mistake is placed.

The course if good, but i believe the content should be more didactic.

Lectures are not easy to understand. It almost feels like they plucked various sections from a longer course.

exercise are too heavy

The approach in this course is incorrect, I think that will be a course with more concret examples, but is a course with a lot of teory that is not applied.

This course is definitely too low level for me, it is also very scientific computation oriented. It was an interesting parenthesis in this cursus, but not with the time taken. Lesson emphasis too much on specific implementation tricks, and are sometimes hard to follow. Also coding style differs greatly from coding style of other lessons (lots of mutability, intensive usage of explicit loops).

It's difficult to follow the content. The way it is organized could be greatly improved.

The course presents two core approaches to parallel programming - task and data parallelism. While these concepts are really useful, I expected more details on, for example, how to implement the _parallel_ construct used throughout the lectures. The materials were good and I can use some of the ideas straight after the lectures in my everyday coding, but the assignments were really slightly related to the topic.

Barnes Hut simulation assignment. I'd say it has nothing in common with parallel programming in Scala. It looks like the authors looked for some real-life example or use case for Combiners and this simulation model looked nice. But, really, does any developer not working in university would ever use it? It's completely impractical, the most of the time I spent reading the description of simulation model, but the coding itself was just playing with 2D coordinates and some basic recursion. I'd expect something more practical, e.g. implementing simplified form of Hadoop map-reduce or something like that so I can use it after the course. But Barnes-Hut is too specific and is pretty far from everyday problems developers encounter.

While some the material was useful, I was extremely disappointed with this course. The first two lectures were nearly intolerable to listen to, and the last assignment was very poorly designed and documented. I would not recommend this course to anyone unless it was significantly redesigned and updated.