學生對 华盛顿大学 提供的 Communicating Data Science Results 的評價和反饋

yikes update the github resources please

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.

Great class !

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.

very good course for learner

Excellent thoughts and concepts presented.

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.

Too little people participated and long peer review time.

But the course content is good.

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.

Excellent content. Detractors were some of the lectures had a continual popping in the audio and the instructions for the final assignment seemed a little dated and required a bit more work to figure out the correct steps.

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.

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.

First professor was incredibly good at giving an overview over design choices in data visualizations.

Second professor sadly somehow spoke too fast and had less of a red thread through his presentations.

The first and second week of courses were good, the third week however was too hypothetical and one-sided.

Nice course into data science

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

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

Very interesting subject. Nevertheless the training course material is too theorical.

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!

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

Nice course

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.

OK, but obvious for someone who has worked with data science.

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

The assignments for this course are outdated and not well supported.

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.