Really disappointed by his way of teaching. He assumes we know every thing before hand, database, server etc. He just has basic concepts in his lecture classes while intermediate level implementations of it in different languages. He just instructs check out this tutorial online and do this assignment.

If you are already familiar with all the languages and software platforms that he is using than you can go ahead with the course or you will end up like me where you will have to take up different courses to just complete assignments of this one.

yikes update the github resources please

I wish there is a coherent explanation of procedure to do graph analysis on AWS. The required details are provided in bits and pieces in the discussion forum and in github. I had to spend a lot of my time figuring this out. If you are new to this be ready to spend a lot of time or better take some other course where all explanations will be provided. But if you have some experience then this course is great.

The material was very general and I think a little bit superficial especially the first week concerning visualisation. There was very little connection between the videos and the actual required skills for the assignments and although I like learning by doing a little bit of guidance would have been nice so that you know that you are doing things in the best or most appropriate way.

The assignments for this course are outdated and not well supported.

Guest lecture is interesting, other lectures are of quite low quality

Not really the same quality as the first two courses in this specialisation. The lectures videos are somewhat disconnected from the assignments.

very good course for learner

The information from the last assignment is split into Forums and Tasks description. This is very easy to fix and not doing it shows passivity from the organizers

I took it when the specialization was just a single, 12 week course. The assignments are barely updated and you have to rely on instructions found in the forum. It has audio quality issues as well. Otherwise, the content it top notch.

The course does not has lecture slides that is better for students to understand.

The big assignment at the end contains instructions that are outdated and incomplete. Given the length of the course, it feels like you already need to know the material before even taking it.

Nice course into data science

The peer-review assignment is not properly designed. From my own experience, colleagues tend to underestimate other people's projects. In addition, the peer-review had an extra/optional advanced component (analysing criminal patterns for a second city; comparing patterns across two cities), which I carried out but got no extra credit for. The extra work was not even part of the assignment classification -- there should be a bonus question for students who carry out the advanced part of the assignment!

Great and useful first week about visualization, although I wish it would cover more material . The ethics and cloud computing felt somewhat incomplete, but useful as well.

Good class, very effective hands-on homework tasks. One thing I found is that the time for homework is very underestimated by course creators. It takes much longer to complete the tasks than indicated and within time given. Otherwise, very happy with taking the class.

The instructions are very good, and it's nice to work on real big data. Also it is very helpful for hearing information about how a data scientist should consider problems carefully. Without taking the class, it wouldn't be easy for me to rationalize for example cost and sensitivity issues.

However I took out one star because of the instruction for the final assignment being out of date. Although the task it self is not too hard to figure out. The initial instruction on how to start using AWS was outdated.

I was very upset by the end of this course. The documentation was terrible. I ended up spending way to much on AWS even though I managed it the best I could Terminating instances. In general, I think this course would have been more fulfilling if the documentation was appropriate.

This course is really bad. The instruction is not enough to solve the programming assignment. The almost contents aren't related to communicating data science result.

I'll say the same about this class as the rest of the specialization, if you have the skills to complete this course then you don't need to take this course. If you don't have the skills to complete this course, you will not complete this course. The course instruction is at 10000 feet level and the assignments are very challenging and the course will NOT teach you the skills required to complete the assignments. The AWS final assignment is a very much throw you into the deep end with no real instruction (well at least completely outdated instructions) and will expect you to swim (or more likely for most people, to drown).

I recommend the Machine Learning Course (from Bill's colleagues) at University of Washington. That is a course where you get some real instruction and understanding of how to complete assignments (though still very challenging).

Excellent thoughts and concepts presented.

Very good exercise to pick up PIG and AWS environment. It is best to pick up jupyter notebook prior to taking this class for the first exercise. I like how David has been able to present so much content in a 3 weeks lesson.

This course is not maintained. It's flat out exploitative to throw students at an AWS assignment without updated instructions and with outdated versions of pig scripts, etc. They're setting students up to hemorrhage money on AWS and possibly not get anything out of it. Under no circumstances should you take this course or even this specialization so long as this assignment is gating it.

Much of the assignment was out of date. The content was not related to big portion of the assignment. There was no way of getting clarification over the outdated assignment content.

Nice lectures with lot of good information. AWC setup instruction need to update according new AWC interface.