Several exercices do not work as described, with error messages.

Explanations of what we are doing are light.

Too focused on GCP. Could be more on DL itself.

Videos were too short. Explanations of the key concepts were really poor. Quiz in week 1 had error that was raised by the user 6 months ago and it is still not fixed. Coding section had library mismatch that led to errors. The presentation of the materials were good.

This was a very interesting course on NLP and Time Series. My only concern is that some notebooks worked for python 2 mode and not for python 3. Also, the tensor 2 tensor lab could not be completed in 2 hours, as some of the training may take more than 3 hours to complete.

Overall, good information, great technology and great teachers.

Thank you.

One star, but not to content. But because the course don't have "Audit" option. It's mean that after subscription ended and you received certificate, You can't more access to video material in course. When subscription active, You can use mobile application and download video material for studying offline. Before yours subscription ended, copy video material to safe place for later review.

p.s.

But the course content deserves a higher mark - 4-5 stars. As others courses in this specialization

Maybe this course was too advanced for me. I did the other course on tf and that felt too easy. This was unreasonably hard. There was no explanations at all before labs and there were like 5 labs a week. how are we supposed to do them? i skipped nlp entirely, because i could not follow it at all due to zero guidance and explanations. The only skill i got from this course was to copy code from internet, but i could do it before

Subscribing to this course only gives you option to run assignments on Qwik labs, and they're very poor for these kinds of assignments. You won't get any feedback on assignments anyway since there is no grader.

If you want to check out the material it's better to just clone training-data-analyst from github and do these assignments on GCP free tier.

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.

Amazing course, I also took a bunch of other Deep-learning and specially Sequence Modelling courses from other renown instructors and institutions. However, this is so far the best. better than all of them.

1- Very well structured

2- Fairly advanced in contents and techniques

3- Reasonably challenging.

4- Full free access for a trial period ( not all courses offer that)

5- Access to GCP for free

Amazing course, well done Google

Excellent Sequence Models explanations and examples to learn from, I quite enjoyed all the fantastic tips and best practices recommended by Google, looking forward to the next course in the specialization.

Great way to practically learn a lot of stuff. Sometimes, a lot of it starts to go over head. But, it is completely worth the learning curve! Definitely recommend it!

I have only one remark, please improve lesson regarding NLP by includin model build etc.

Otherwise course is excellent and was helpful for me

I like it because it is very relevant to my work. The dialogflow part is a bit weak. I am not sure if it is the product or the course.

Awesome course, Great tutors they teach tough topics very easily like RNN(LSTM, GRU), Encode Decoder and attention.

This course is short and sweet, and covers many helpful usecases of GCP tools related to the course topic.

Everything was fine except the solution videos are old, that why you should update with update code.

this course is helpful for learning sequence data with tensor flow ,Thanks for this course

Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.

Lot's of good information. I cannot wait to start using this knowledge. Thank you!

A Very powerful course

Thanks for all google team

Excellent coverage of a complex topic

Very good course to start with NLP.

Quite a challenging course so far.

Excellent topics and flow.