The course content is fine. My big beef is with the last lab. Does not, will not run on loading the data. I experienced so much trouble that I looked into some guidance with the answer video. A character by character exact copy of the solution will not run to load the data. Total waste of time.

Yes, I realize that I was "cheating" by using the solution as my input to the lab. But after having tried (and failing miserably) to get the answer on my own, and not even being able to get past the very first hurdle, I had to try to get something working. I soon found that it wasn't just my lack of experience, since the provided solution did not work either.

Google has clearly put a great deal of effort into constructing and polishing this course. However, the certificate is really nothing more than a participation trophy. I understand that putting the course materials (videos, demos, etc.) are time-consuming. An exceptional course, though, needs to actually test that the learner has, indeed, learned. When all of the labs/assignments require nothing more than clicking through them, they fall far short in this respect.

The instructors were talking most of the time in a monotonous way without showing proper slides or elaborating the materials. Overall it was a very poor introduction of the ML. The two labs were good, however it was surprising to me that they did not commented out the notebook codes!

Maths and ML stuff are explained very poorly... very rushed and people speaking are clearly reading from a script which makes it difficult to understand and follow on =

instructor more plain and hard to hear so many math concepts just with words not visual enough, seems like instrctor is not breaking it down like the first course.

At least make sure that all quiz questions have been mentioned in the course materials.

stochastic gradient descent is ONLY in the quizzes...

The LABs in this course did not work for me. I was not able to open DataLab in my Lab sessions. This is quite frustrating to me.

Labs are slow and very shallow. Quiz questions are often either unclear - or the provided answers are simply wrong.

The labs really just lay everything out for you, and don't challenge you to learn anything for yourself.

It's covering a lot but brushing over things too quickly and using a ton of jargon.

Weak: Long on telling you how great google is, short on technical skills.

These are plain lectures. Ng's are way better.

No real implementation

labs not really useful

Barely learn anything

It's unclear for who this course is meant. It mixes basics like train-validate-test with lectures that use machine learning terms that only have meaning to someone who has already knows ML terminology. If you're looking for a good introduction to ML - check out Andrew Ng's course.

"Short History of ML" was good, if kind of light. The rest of this course is flaming garbage. Zero topic organization. Material is poorly explained. Labs are poorly detailed and in some cases don't work out of the box. Seriously, skip this course and take Andrew Ng's instead.

The notebook based demos are unfortunately pretty useless as labs. All of these courses would be much improved with real labs that require the student to build the system.

Pros: Tensorflow is an excellent framework for deep learning

Cons :

1- The way this material is designed is 10 X SHIT

2- Either teach properly or don't teach at all.

I'm not able to access the video lectures even though I purchased and completed this course 6 months back

Too much scary information provided at once combined with the mindbending sql queries and data parsing

This is the most superficial course I have ever taken. I just waisted my time.

Did not learn much! Poorly instructed courses.

not well structured and lack handouts

No hands on learning.