Nov 26, 2018
It's a pretty interesting course, specially that's the only one that teaches featuring engineering with a focus on production issues, but it assumes some knowledge with apache beam, and dataflow.
Jan 10, 2020
i really like the effort taken in developing this course, the structure. Kudos to Laks for converting lots of statistical and coding language to very simple understandable english.
创建者 Alejandro O•
Jan 15, 2019
More hands on activities is the common theme on all classes, its a lot of talking and not a lot of putting things together, follow the University of Michigan Python curriculum, that one is great for hands on learning.
创建者 Leszek Ś•
Aug 13, 2018
Please update instructions. UI has been changed.
Some code doesn't execute. Last lab. Should be updated. This can be just one sentence (simply, versions of packages don't fit).
创建者 Super-intelligent S o t C B•
Nov 12, 2019
This wasn't a bad course, but it is more geared towards showcasing GCP features (BigQuery, Dataflow, Apache Beam, etc.) rather than teaching feature engineering.
创建者 franco g•
Jan 06, 2020
The course focuses much more on the gcp tools rather than the feature engineering, labs were not easy to follow, some pieces of code did not work properly.
创建者 Alouini M Y•
Sep 16, 2018
A good course overall. However, the last two labs didn't run since packages couldn't be installed. Please update these labs. :)
创建者 Sandip K M•
Nov 26, 2019
Some of the Labs do not work and the information provided are not enough to debug the issue.
创建者 Arturo M•
Nov 20, 2018
Too long for one week. I would suggest to split it in two or even three weeks
创建者 Carlos B•
Dec 20, 2018
The work needed was waaaaay below a one week
创建者 Matthew S•
Aug 05, 2018
Some missing steps in lab descriptions
创建者 Xinyue Z•
Sep 14, 2018
Some labs don't work
创建者 Cooper C•
Jan 16, 2020
I feel that this, and the tensor flow course that proceeds it in the specialization, were a waste of my time. My feeling is that this entire specialization is a glorified demonstration of what GCP can do with ML. The labs are not interactive and in some cases did not work. I don't feel that I have learned anything new. If I were to use GCP for ML purposes, I would need additional training to do it. I don't recommend this specialization.
创建者 Alex H•
Oct 21, 2019
Great instructor but (1) the coding challenges are buggy and don't really teach you anything and (2) a lot of the material in this course is tedious for someone with professional training in AI but no experience with GCP
创建者 A A•
Nov 08, 2019
the lectures are good, can be boring. The course would have been more interesting if it had thought-out assignments instead of demo-code to just run as labs
创建者 Thibault D•
Sep 14, 2019
The gap between the lecture and the coding is too big. The coding sessions need to be more interactive to be useful.
创建者 Marko H•
Apr 06, 2019
Basically this course would receive four stars, but repeated problems with qwiklabs had a severe impact on my overall experience. I got thrown out three times in a row (and my account locked) during dataflow lab.
Every time I had to request unlockin of my account, which took half a day every time. When requesting advice to avoid this error, I got offered the general and vague explanation that I "should only use the resources required by the lab". I am 100% sure that I didn't use any extra resources, including zones and regions.
The Coursera's helpdesk went behind the excuse that Qwiklabs is a third-party service. That may be the case, but since Qwiklabs has been integrated into the Courseras' course, the ultimate responsibility lies with Coursera.
I hope that Coursera will co-operate with Qwiklabs to sort out this very annoying problem.
创建者 Nathan K•
Oct 29, 2018
Ultimately I found this course to be disappointing, because the Google APIs for DataFlow, BigQuery, etc. are unusable with the provided QuickLabs account. When you try to activate any API during the labs, it asks you for a location. It is a required field that says: "You must select a parent organization or folder." Clicking this option reveals a single organization called "no organization," which is not a legitimate choice. APIs cannot be activated and then cannot be used in the lab.
Because of this I was unable to actually do many of the labs that required the use of the Google APIs including the keystone lab "Improve ML model with Feature Engineering" where the taxi-fare prediction model is refined into a perfected state.
I'm upset that I paid money for this.
创建者 john f d•
Jul 18, 2018
Labs vms are to slow. Speaker is difficult to understand. Mic varies and speech pattern is not clear. The presentations need some graphics rather than a guy talking. Sketch out the ideas on a white board rather than talking 5 minutes to a single slide.
Oct 07, 2019
this is useless...google is advertising their product and making us pay for it. They should learn dr Andrew Ng and create courses which teach us without using a specific platform.
创建者 Arman A•
Apr 11, 2019
Pros: Tensorflow is an excellent framework for deep learning
1- The way this material is designed is 10 X SHIT
2- Either teach properly or don't teach at all.
创建者 yannick t•
Jun 11, 2018
Not very clear + lack of real student practice