Pros: The content of the course is great. It introduces fundamentals of big data technologies to those who are new to this field, with some hands-on practices.

Cons: The instructions of assignments are not always clear - they are corrected in the discussion forum but why not updating in the assignment page? Usage of Python 2.7 is also somewhat out of date since it's 2019.

Biggest con: The way the lecturer talks is more than annoying. Full of stop words like 'fine', 'ok', with occasionally correcting mistakes on slides or diverging to other topics - there are only a few minutes each video and how much time did the lecturer wasted on talking nonsense? It's fine if he talks like that on some 90-min-long classes but it's on Coursera. Sometimes I just skimmed the slides rather than listen to him.

It's pretty tough in assignments especially when there are mistakes in the given description, but I do learn the basic concepts of relational algorithm and MapReduce from them.

Assignments need to be updated, but the material is solid!

Very wide and fundamentally robust introduction.

Very good course for understanding the underlying logic behind emerging big data technologies

Good information but lectures were poorly produced and unedited and exercise instructions were blatantly incorrect several times.

A very good introduction to skills needed for applying data science ideas on large scale data problems.

Thanks for this course.True Parallel computing example would have made it even more awesome .

The material is good. If you can get past the instructor's mumbling and rapid speaking then you'll be okay.

Quite interesting subjects, but video material is not of high quality and many mistakes are not changed in later sessions but altered via a text in the screen of a note on the next sheet.