I enjoyed this course, but I believe there are some errors in the grading code related to interpolating colors. I raised an issue about it on the week 5 forum but never got a response. The project was interesting, but it would have been nice if there was a way that we could have been a bit more free in how we designed the interfaces. If you were trying to use something like a spark RDD it made it pretty cumbersome, having to always fit everything to an Iterable at the end. ALSO, I tried to add a library when I was doing this to add the shapeless library to this to add some interesting features which would have made the code a lot more general. I spent days getting it to work, only to realize you library dependencies are not actually imported when you submit, it only runs with the base ones that were pre-defined. A warning about that would have been nice.

The first couple of assignments I found harder than the rest, and also the best bits. I found myself enthusiastically telling my colleagues about the data files and the spark code to join them. After that it got a bit too simple perhaps. And a little contrived. Some of the curried functions you had to fill in were way different from what I'd have written if I'd been staring at an empty screen and even after the course I've still not learned why I'd want to use this setup. The Signal bit in the last assignment was just plain silly, I think. It remains completely unclear why you'd want to use Signals here, other than that you want to refer to materials from the reactive programming course, and the sample code for the update doesn't actually work because the update method is protected.

Milestones 1-3 was OK but milestone 4 require a much more efficient solution. And the only info grader gives you is the message about timeout. It would be better if requirements for milestones 1-3 were harder to fullfill or milestone 4 would not depend on previous code. But it depends and if your solution is inefficient it's very painful to search the problem all around the code. It's offered to use spark and other tools in this project but using spark is also painful. I get inconsistent result from grader with occasional OutOfMemory exceptions, but this project cries to be implemented with spark. I've learned something during this course but it was too stressfull and painful.

You will learn a lot of geodesy and some interesting numerical mathematics, but no so much Scala. As far as I understand Spark has no official support for Scala3, only through workarounds that do not support everything (I have spent quite some time trying to make Spark work the way I wanted, but I have failed). If a test fails, the logs are basically useless. Generally, this course looks as unpolished as other courses in the specialization, reflecting limited resource available and invested. The Capstone is particularly frustrating, since you will not learn any new programming concepts here.

I'm sad to say that the last course in the specialization was the worst. The grader functions made it quite cumbersome to use Spark, which the test of the specialization was about.

You cannot use Spark throughout the course, because of the grader functions. You have to jump in and out of the Spark domain, which hurts performance and will not allow you to write a complete Spark program.

Would have liked more tests provided with the capstone to supplement often vague specifications. Feedback from autograder is often obscure as well as it refers to some input parameters of the randomized test - hard to take guidance in code improvement from it.

Tough to design a capstone for a course, but I was never really able to get excited about the capstone project. It felt tedious. Not sure if this is the course organizers fault thought...

More about number crunching than fp. The dataset is within the jar, which caused a lot of problems and excluded efficient solutions (and the course is about efficiency as well).

Creo que los ejercicios y trabajos deberian ser mas de aplicacion que de algoritmia ya que no permite analizar más los métodos que usaras en vez del algoritmo.

I have finished previous 4 courses, they are excellent. But this one not easy to understand, doesn't have some simple test cases.

Lots of ambiguity in the course assignment, especially the 5th week one. Also response from teaching staff is very poor.

Overall I liked the course but some of the grading output was hard to understand what exactly I was getting wrong.

It was too algorithmically and math heavy. Also, it would have been good to have more videos.

Good project but instruction is a bit draft. Probably because I joined their first ever one.

too much UI

No good explanations, no mentors, everyone survives on their own. For the life of me I cannot pass farther than week 4. Sometimes instructions even make it worse, so you are left to experiment and try to understand, that you do not need to listen. For example, there was 1 time when they showed alpha = 0, thats it, so I assumed that I need to leave it be. But it turned out that that would make all colors transparent and grader whould signal wrong coloring. Yes, I could have guessed, but it was not obvious. The grader timeouts and there is no optimization I come up with for me to pass this course. Such a pity as this is a great way to test your skills, but there is no guidance on how to improve them.

I appreciate how hard it can be to write coding assignments. Especially in this case it seems as though the limitations stipulated by Coursera may have been quite restrictive for a big data spark project. However, I was really disappointed with this course. Rather than getting to test out my scala/spark skills I found myself trying to shoehorn functions into the methods provided by the grader only to have them fail unexpectedly with little feedback. Some more pointers on how to setup appropriate unit tests would also have been quite helpful. It seemed not so straight forward for spark.

There were too much ambiguity in the assignments. The structure and definition of the assignments made it unclear and difficult to solve with some of the included frameworks. It would be a lot better having a stricter definition and limit it to one or two frameworks that were suitable for the specific definition of the assignments.

For a course that requires you to work on your own project, it still forces you to follow a code skeleton outline. This limits the freedom with which to tackle the project's issue. There is not much guidance or support from course organizers, which makes this course not very educative.