Thank you again for your time and for create this course.

Again I think this course should be part of the introduction of big data. Like in my past review, you make a lot of references to pages and you just scratch a little part of the content.

This should be a interactive course, reviewing commands and programing, instead is theoretical. And in my opinion no very thick.

The only interactive part was the Spark session, but my complain is Spark in not part of hadoop, besides, it's to big that it should have it's own course.

Again thank you for your effort and your time.

Lectures not presented well. Assignments not explained correctly and lack of information from lectures meant more use of the forums than should be necessary. Couple this with quizzes having incorrect answers (as in not the facts) this whole course was disappointing and this specialisation is not getting any better either. Someone needs to audit these courses better. I have done a Spark course on edX that was so much more helpful, informative and useful. Letting you learn by doing in a MOOC is key and these UCSD courses miss that point entirely.

Sort it Coursera.

The speaker is hard to understand because of the dialect, the english subtitles are often flawed in importen pieces and the agenda chosen is confusing. A lot of specific knowledge about different features. Bur how about explaining the central parts first better. If I was to teach you about a tv. I wouldnt start of by telling you about it's features from a to b. I would tell you about the basics. I mean you can watch different channels, by changing channels, you can turn up the volume. And you use it for leisure.

Assignments for MapReduce join was not phrased in a proper manner.There was no assistance from any support staff in cases where multiple submissions were rejected. The criteria set initially was "no programming experience required".How do you expect students to code in python sans any asssistance and pass the assignments.

If you want to see how a tutorial should be designed check David Tran post and see how well he explained the assignment.This was intructor's job and not of the participants.

The overview and conceptual explanations are good. However, by week 3, there is a significant amount of programming required with little explanation provided. In spite of assurances that you don't need programming experience those assignments will be difficult to successfully complete if you have little programming experience. Required syntax is never provided and you need to spend a lot of time searching for the answers on the internet before you can write the correct code

Information in the course is barely systemised, any listener would have to add any other theoretical base to lectures given here. With all that preparation on week 4 there start programming assignments which become a dead-end for majority of learners. Before taking this course at first take any Python course and HDFS/MapReduce course to understand what would be going here. But why should you take this course after you already know the stuff?

the course was by no means intended for attendees with no previous programming experience - it was grossly misleading - python and spark assignments were very demanding albeit interesting.

it is not always easy to listen to the lecturer with a heavy accent - even though it seems that

they command the knowledge they are presenting. i would rather have one lecturer per course

or at least all the lecturers having the same native thong.

The theory provided is good. It all gets bad when it is time to practice. The course relies on works developed by others, like Cloudera's tutorial which can be done on our own. The most irritating part is the assignment on the "found everywhere" wordcount example. There would be a huge gain in value if the instructors developed their own dataset and examples, to provide a real addition of value beyond what can be found elsewhere.

-- Beginner course, not very deep

-- First four weeks where a bit dull, firth week was good (second star).

-- Repeated explanation about the Hadoop ecosystem and tooling without depth.

-- Questionary: Reproduction of random words which were told in the lecture.

-- Improvement proposal: Way less questionary and more programming assignments.

-- Help is provided with programming assignment, although programming is not that difficult.

Poorly made and redundant videos and powerpoints. Having the lecturer on the screen with a powerpoint background was distracting and never improved comprehension. Many videos rehashed other videos from the course or from the previous course in the specialization. Take this with a grain of salt as I have chosen to bail out early. It may improve with time, but I am doubtful and do not wish to put the time in to find out.

Lectures get tedious when the lecturer uses the word "Um" too often. Would be better to rather take the time to clean up each lecture and re-edit for grammar, clarity, simplicity, enthusiasm, etc. Remember to smile; You only need to get it right once and pow; you're famous! In this sort of learning, every second counts and the quality of your product will become critical especially in the face of your competitors.

There is some good material in this 2nd course, however, some of the lecturers are very difficult to understand due to his accent. Also, the captions are very inaccurate and at times gives erroneous transcripts. More importantly, the classes don't go into detail very well. They keep repeating the most general points about Hadoop and hardly go into the level detail to get a firm grasp of the material.

The course is okay if you are just taking it for fun and as a hobby like I did. If you want to learn seriously this is not the course for you. Lectures are poorly organized and the heavy accent of the instructors make it a pain to listen to. I am not a starter in Hadoop framework but I found some concepts poorly explained that even with background knowledge it was difficult to understand.

Last two of three lectors just read material from papers and have low oratory skill. In result course became boring and was hard for me pass. Difficulty is pretty low, but you need to have some python skills to pass (this isn't mentioned in course info) and discussion forum full of people who is struggling not with course problems, but with basic python questions.

Having multiple instructors means that there isn't enough continuity in this course. They are sloppy about when they define terms, there is an expectation that you know Python to do much of the course work even though it is not a prerequisite. Also the pacing is not very regular. In particular the last week is really bad. Try to do that week very early.

Some course information was just wrong (ex. claiming Cassandra was part of Hadoop), frequent broken links to course materials, and the starter code/suggested approaches for assignments were poor examples of good engineering (ex. recommending combining heterogenous data under a common key and differentiating by calling isdigit).

Poor experience with this course in general. One instructor just reads the slides, another says mostly "um" then murmurs something under his nose, all of them mostly look away instead of looking at me (camera). Volume level varies from video to video.

Really deserving 1 star, but added 2nd star for interesting assignments.

The description for this course says it requires no prior programming experience. However, the hands-on assignments require Python, in which the course provides no instruction at all This would be a good course for someone with a basic background in Python, but very frustrating without it.

Programs were not fair for novice programs or business people. Real confidence breaker for people and I do not feel it assisted the knowledge of programming. The slides for spark were also lacking in details to properly solve the quiz. Teacher never looked at the camera only the notes.

Homework and quizzes are difficult for the wrong reasons: lectures are inadequate to the material, and questions are often poorly designed or worded, fluctuating between rote regurgitation and blind groping. You will be given exposure to the concepts rather than an understanding of them.

The week 2 module on HDFS architecture was awful and the week 5 module on Spark was even worse! Those professors need to be replaced immediately with people who know the material and are able to articulate it better. I gained nothing from those 2 modules but a headache - unacceptable!

Modules 4 and 5, with actual programming exercises are much more useful than the first three modules. The quizzes simply do not add much value for those of us who are taking this specialization to get some hands-on experience with big data analysis. More programming applications please!

more than a few times i've wondered if the instructors were just reading the tutorials and screencasting their progress through the tutorials. the quiz's were poorly phrased and the slides seem like they're as quick a cut and past as can be assembled to meet the posting deadline.

Python skills are required. I tried very hard getting to learn and understand the required tests; the practice and then tests were written poorly, difficult to understand. If you have no Python skills I would advice against taking this course and spending your hard earned cash.

The course is a good intro to Hadoop components and architecture.

Every video ends with asking to go for certification, quizzes are not for those who hasn't paid for it. The course seems to forcing students into purchasing the certification and experience is not pleasant.