This course covers a lot about the data pre-processing, and the tools available in Google Cloud to enable the gruelling tasks. Thanks very much for the lectures and training labs. Very informative.
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.
By Emily T•
This course really needs more hands on work with code, but it was still good and I learned lots.
By Sandeep K•
this was really good, except removed one start for trifacta integration of dataflow lab.
By Nagireddy S R•
Felt like it was cut short at the end. Would like to see a bit more on the tf.transform
By borja v•
the course needs some code upgrades because of ML engine is close to be depecreated
very nice course , -1 star for no pdf/ppt notes made available
By Alexander Z•
great content and cool notebooks ... sometimes hard to follow
By Marcos H•
Very practical and Lak is a great teacher and communicator!
By Fernandes M R•
Maybe a little more example of how deal with features.
By Malithi N•
This course explains theories nicely with labs
By Joel M•
good clear instructions, and valuable content.
By Anupam P•
Comprehensive yet precise and clear.
By Rohit K A•
No course material for reference
By Michael C•
Very important information here
By Rahul K•
Lovely Course. Thanks Google
By Ripunjoy G•
Labs have problems
By Rohit K S•
By Abhishek S•
By Terry L•
개요를 알게 되서 좋음
By Benjamin F•
By Ahmad T•
By Yingchuan H•
The content of this course might be a bit too much for one week compared to previous courses in the specialization. Also, it would be great if some of the labs are more clarified and introduce more opportunities for students to participate in writing code for the lab session rather than just going through it and running existing code. I did experience some issues installing the tf transform package for the last lab, which might not be a common issue, but was kind of frustrating as it prevents me from more exploration of the learned skills. Thanks for providing the course anyway. I learned a lot from it.
By Fabrizio F•
The subject is very interesting and I was alwyas curious about how Feature Engineering should be done with Tensorflow. I come from Pandas, where feature engineering is not that difficult, but with Tensorflow it is different and not that intuitive. Here in the course three different ways are presented. I guess I'll have to study more Apache Beam.
By Jonathan A•
The concepts were taught well. However, a lot of code and cloud interaction was involved, making the labs a key piece of the material. Two of the labs didn't work because the Google lectures aren't up-to-date with the Google APIs. Although Coursera response to the bad labs was prompt, the Google team did not respond.
By irfan s p•
maybe this course is very good, but for me I really hard to digest knowledge from this course. It needs a lot of time to understand the theory. Maybe it will be good if the course is given in more videos and slower pace. Thank you
By Alejandro O•
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.