Learner Reviews & Feedback for Big Data Modeling and Management Systems by University of California San Diego

good cource

Tool !

Good

Interesting course and valuable theoretical notions. However, i would have preferred that it contains more practical (challenging) tasks especially that most if not all classmates have sufficient IT background and the hands-on were too simple. Moreover, it is easier to understand theoretical knowledge when we apply them in practice. The course creators might have thought to leave all challenging practical work for the final project but i would suggest to include mini-projet at the end of each course. Another point regarding the final assignment of the 6th week, it would have been better to do something similar before it, many classmates and I were confused and unsure about how to answer some questions and we had to evaluate each other's work while being unsure if our own submissions were correct or not.

As far as the content is concerned, this is a very good course. Concepts are explained well.

What I disliked about the course is the final peer-reviewed problem.

1. The instructions were unclear about what was needed to be done.

2. When submitting, the HTML of the problem got badly garbled.

3. When reviewing peer submissions, for the first part nobody could read their submission because of the garbled format.

4. Most people did not get the second and third questions right but instead of there being a way to evaluate how much they understood, it was a yes/no option to grade them (which amount to either them passing or failing).

I think this is a promising specialization but the instructors need to pay heed to the bevy of complaints in the various forums.

This had good information logically presented. However, there are two hands-on activities whose instructions have been out-of-date and incorrect since at least 2016. It is not possible to complete these hands-on activities by following the instructions, and no one on the discussion boards has been able to come up with a solution. The hands-on exercises are very important to allow a learner to reinforce and solidify in their own minds the lessons. Without them, the value of the entire lesson suffers. And if the hands-on exercises are not ever being updated nor corrected for errors, how do I know the other course material is still accurate and relevant? It seems updates to the courses are not made.

Great coverage of the course materials through the readings and lectures. I have given a lower rating because the hands-on exercises did not work for me where the custom Python scripts were needed. The majority of the scripts wouldn't run for me because of dependency failures. Using a VM image specifically intended for the course and scripts, I should not have had this issue. I was able to understand and complete the related exercises by watching the videos for them, but it would have been nice to be able to perform the exercises themselves. Seems like the python scripts were perhaps written by an intern/grad student many years ago. Perhaps it is time to revisit them now that many years have passed.

The course in itself is quite good, although there are many concepts presented in a few videos only.

The bug flaw is the final peer review assignment. Questions are unclear; It is a pain to complete. When reviewing your peers, expect the same issues: you are left alone to interpret if what was done corresponds to what is expected. I guess instructors intended to make something simple but it is definitely not.

And the most frustrating thing is that this has been a recurring complain (see the forum), and nothing has changed so far.

1. The course is very general and high level introduction.

2. During the lectures there are some examples that in some cases are presented as very small images and briefly. I personally could not understand some examples presented in week 5.

3. I found the hands-on lectures very helpful. I wish there was more that would delve into more examples in more details.

4. The course was very overpriced given the amount of information offered compared to other courses I have taken at coursera.

Thanks.

The topics addressed in this course are very valuable and cover a wide range. The presentation of the material unfortunately often misses clarity and sufficient detail. Backup material with a concise treatment and optional readings would be helpful. In addition it would be good to have several guided exercises that train hands-on skills, show practical features and integrate topics. The final assignment fits in this category, it however comes late and as a hike.

A good course taking into account that it does not require previous knowledge. I am giving "only" 3 stars because for a basic (no previous requirements) course I would expect much more additional readings. On the other hand, if you have programming or database experience you will find some topics too "basic".

I have liked it more than the first course on the specialization but I would expect more details (I think general topics are well explained).

I really wish I could give this course more stars, the content is great and well delivered and at a perfect level for someone like me who last worked with big data sets when 20Mb was absolutely enormous and Windows 3.1 was cutting edge technology. But and this seems to run across the whole specialisation, support from the course team varies between very patchy and none at all. Technical questions aren't answered for days if at all.

Good information overall, but the "peer graded" assignment at the end is poorly designed and seems unnecessarily arbitrary. Not a clear value add over a "final exam" format to justify waiting days for someone to "grade" your work. Instructions for this assignment are poorly written and unclear - for example, completely NOT clear you are asking us to identify a primary key versus stating there is no primary key, etc.

Though it contains useful concepts, the "hands on" assignments are not very instructive. I understand that the course is intended for general audience and programming or doing serious analysis might be out of its scope, but it falls short at providing a basic standing ground from which the learner could improve. Overall, it feels like the assignments and the lectures are intended for two disjoint target groups.

The course was okay, but the last Peer-graded Assignment was totally unclear. A lot of other students reported this problem on the discussion forum, but nobody handled this. Some students tried to ask questions, but any menthor answered back in merit. Of course if nobody understand the task then how can we rate each other? It is not fair. I think some examples can help on this problem.

I feel the assignments were a little vague and such assignments should be reviewed by mentors and not just fellow colleagues. Also, the concept on which the questions were based, were not covered that widely.

Additionally, if someone wants to refer to the slides in future they should be able to get the information they want from the slides itself, so they could be made more descriptive.

This course offers very useful high level overview of concepts and ideas which make you feel confident in the long run. However, the course is extremely basic and does not go deep beyond the high level concepts. The hands on exercises are boring and do not engage students. The course needs to be improved to make it more useful for students. This course is not very worthy of the money.

This is ok. There is some light theory and application of it, but even less hands-on. There is also too much of an emphasis on different big data systems and each brands specific uses. This is good information, but I think it could have been presented on a two page comparison chart. The next course is supposed to be more more hands-on, so I am looking forward to that

Thanks for offering this course. The course is not so good because most of the portion is theoretically based. We join the Coursera for hands-on courses. We study a lot of courses in our Homeland universities which are 90% theoretical. so I join Coursera to implement the concepts practically but this course is not so practical.

Definitely could have used more hands on practices. The hands on practice examples could've delved deeper into 'how' instead of just giving you the command lines to run. Majority of the times were spent on lectures talking about abstract concepts. While useful, more of that time would've been better spend on hands-on examples.

I spent lots of hours figuring out cloudera/quickstart ,however could not install some packages :)

Python 2 is not supported so it would have been nice to make some modifications as well. In the videos you are stating that the domain is changing really fast, while you haven't updated martials accordingly.

Fairly superficial treatment of a wide variety of topics. There was only a loose connection between some of the hands-on exercises and the lectures. The final assignment questions were not clear and the marking scheme was vague, which led to quite a bit of confusion while answering and grading it.

Although Content quality was good, the content is too much less and could have been easily integrated to first course or other course in specialisation.

Secondly Quiz were not challenging ,it was just too easy to pass, and this actually takes away the very reason they were employed in this course.

The course is great. The final peer-reviewed project is interesting, but very badly designed. The explanations are fairly confusing, and the peer-reviewed format really doesn't fit this assignement, as modeling can be performed in many different ways, that untrained peers might not recognize.

Expecting more hands on experience with big data frameworks like Hadoop or Spark. Instructions of the final assignment is very confusing, you don't actually know what it really want you to do until you go through all the Q&As in the discussion forum, which is really wasting time.