Jan 11, 2016
Great course that strikes a balance between teaching general principles and concepts, and providing hands-on technical skills and practice.\n\nThe lessons are well designed and clearly conveyed.
May 28, 2016
I like the breadth of coverage of this class. Each of the exercise is a gem in that I get to learn something new also. I would highly recommend this even to experience practitioner also.
von Abhijit S•
Oct 21, 2015
Good Course for beginner in Data Scientist field. I recommend this course
von Gregory C•
Nov 25, 2017
Very good class - the assignments were pretty uninteresting, though.
von Dan C•
Jun 09, 2016
I enjoyed this course and found it challenging. Good job!
Dec 06, 2015
Great assignment and course design! Not easy for me.
von Jeffrey L•
Jan 09, 2016
Very good course! Interesting problem sets.
von Gregory T•
Nov 29, 2015
Interesting intro to some powerful ideas
von XIA B•
Feb 12, 2017
recommend to improve assignment details
von Krzysztof L•
Jul 27, 2016
Good introduction to Big Data systems.
von Sophia J•
Oct 27, 2015
it is very useful but easy enough
von Dario P C•
Mar 25, 2016
Very usefull course. Great!
von Vijaya S K K•
Mar 28, 2017
von Mariano S B•
Nov 19, 2016
von Theo L•
Jan 04, 2016
This course has appealing assignments and covers interesting topics. The course, however, has two fatal flaws. First, the lectures are a bit disjointed. While there is much to learn in the lectures, the lecturers style is a bit halting and scattered (it would have been much better presented if the lecturer had a script to read off of.) As is, the lectures are mediocre, which is unfortunate since the lecturer is clearly knowledgeable about the topics presented.
Second, the assignments suffer from a lack of good error messaging and no support in the forums (aside from what you will find from other students, which can be very helpful at times.) The assignments themselves are a great approach to learning concepts (and you get to work with real data, like the Twitter data), but without good error messaging when you submit a script you pretty much end guessing where you are taking a wrong turn.
I had high hopes for this course, but it seems as though it fails on execution.
von Alexander B R•
Mar 22, 2017
Overall I enjoyed this course and got a broad overview of the various technologies used in big data analysis. The course is video heavy but short on practice. There are 3 assignments the first 3 weeks, then week4 is an endless series of videos. I really enjoyed the assignments but felt there should have been more assessment/practice provided -there are no quizzes to reinforce understanding. The readings provided are mostly academic ones which aren't that clear to beginners (even to programmers like me).
In contrast, a Python data science course on another MOOC platform has 4 times as much content with practice exercises after every video, mid and final exams, weekly problem sets as well as readings.
Ultimately the course showed me what I need to learn next to get into Data Science but the first course hasn't given me confidence that the rest of the specialization will be worth the money.
von Brian D•
Sep 17, 2016
The lectures are all just the right length. As a working professional, it was easy to consume the course in my varying bits of free time. For the most part, the assignments were good. There were a few places where there were mistakes in the instructions or the code downloaded from github had some errors. It was fairly clear that these mistakes have been around for quite sometime, so I wonder why nobody ever bothered to update the code in github or update the bad instructions. This is the internet, not a published textbook. That should be pretty easy to fix. It was also a little disappointing that the 4th lesson was extra long in terms of lectures and had no related assignments. The course was marked as completed when I finished the 3rd assignment so the fourth lesson was effectively optional.
von Dongying Z•
Feb 09, 2019
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.
von Bernhard S•
Oct 29, 2015
Lots of good material, though I don't like how they've repackaged the original material from the prior longer version, which I worked through at my own pace a year ago, off session. Cramming all the material relating to NoSQL and Graph Analytics into the final week without assignment is ineffective. Instead, consider focusing the 4th week on NoSQL, and keep an assignment with it, maybe even the original Pig assignment that required and AWS account. I don't think the nominal charge Amazon will levy would hold anybody up who's serious about learning to process data at scale, it's just a few bucks.
von Stefan K•
Dec 28, 2015
Somehow interesting course about Data analysis. The lectures are interesting for those who have no prior knowledge about the topics, but boring to those who have it. The assignments are quite challenging and the disadvantage is, that they are not connected to the lectures and are therefore not well explained. What I like about the assignments is, that it is practical.
von Eric B C C•
May 28, 2016
Found the assignments were 'very loosely' aligned with the lecture material and had poorly formed problems in places.
Lectures were reasonably good but not quite up to the standard set with other U of W Data Science courses or other University Data Science / Machine Learning courses I have taken.
von Arto P•
Dec 07, 2015
The emphasis on methods rather than specific tools makes the course more resistant to the continuous changes in technology. The stage is set well, and there are practical implementations. Still, it's disappointing to see that errors from previous rounds have not been corrected.
von Hannah M•
Nov 19, 2015
It was really frustrating that the autograder and assignment instructions didn't match. This course has been around too long for that big of a mistake. The lectures were the redeeming factor. They were interesting and presented the subject matter in a concise way.
Oct 29, 2015
the material is too simple. This course is just like a brief introduction, but not a course in college to teach student the real knowledge. I think MOOC course should be the same as a real college course. With the same difficulty and amount of material.
von Martin M•
Jan 05, 2017
Good content for Data Scientists but video lessons are not sufficient to be able to complete the assignments. It required great deal of own searching and trials and errors to complete the course.
von Ingo B•
Oct 10, 2015
This is a cooked up version from an earlier, more extensive course. Lecture videos now split from 10-14 minutes into lots of 4-6 minute videos. It seems, some assignments are missing, too.
von Dwayne B•
Apr 13, 2018
Good information but lectures were poorly produced and unedited and exercise instructions were blatantly incorrect several times.