Assignments weren't challenging.

Nice course! I learned a lot...

Spanish traduction please

Pretty good course

Great course!

learned a lot

Thanks!

Good !

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 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.

This course is quite hard to understand with tasks especially at the end of week 4. I'm not sure that this is very useful now, cause no examples and explanation of current libs in scala for parallel programming, just couple of main classes or methods. From time to time a lot of good examples reg parallelism and associativity, but I'm not sure that we need this kind of deep math and algorithms here in current tasks. This course has academy level of understanding and not adapted for all kind of Software Engineers, etc.

Wrongly assumes that it'll be easier for students to jump from the conventional 'parallel' java paradigms and constructs to parallel streams.

Not a good job on explaining why. It'll require from students some efforts to create the right picture in their minds.

Exercises are great and partially make up for the above mentioned shortcomings.

Some example code is very bad and goes against all the 'good' things being taught by Martin in the first course of the specialization.

Interesting course, but far too short. It ends up giving a quick introduction to some of the aspects of parallel programming. I enjoyed the assignments, apart from last one where the difficulty was more about the context of the example than any parallel programming aspects. That example, extended, could be a good capstone project, but I think it was not appropriate as a course assignment. I prefer courses that follow a book, and this course didn't.

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.

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.

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.

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 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.

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.

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

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

The content presented definitely is good, but in the assignment the things used could be explained in the lectures for better understanding of learners.

Good course and good level on the assignments but needs a lot of improvement on the lectures, specially in the two last weeks.

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