29. Okt. 2018
The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.
30. Juni 2019
The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.
von Clement A•
7. Aug. 2020
Really good to understand the basics, however, it doesn't use the latest TF2 and the exercises are either trivial because too much pre-worked, or too hard because it doesn't give the information required to succeed.
This course really needs to be updated.
von Mladen M•
9. Juli 2020
Programming assignment instructions are not well written (clear), and as a result it is easy to get stuck on something of little relevance to deep learning. Also, I would suggest that you make the lecture notes in written format available.
von Chris M•
21. Aug. 2019
The lectures cover the basic design of the models but don't help teaching you how to actually use them. I learned more by reading blogs to get the programming assignments to work then this course.
von Ashley H•
14. Sep. 2018
Lectures/Videos were excellent, the assignments were very poor (loads of errors in the code not corrected over 7 months since the course went live)
11. Dez. 2020
The course videos were very lengthy and difficult to follow. Many topics discussed in course video were not part of programming assignment
von Simeon S•
18. März 2020
Good introduction to the concepts. Really poor quality videos and exercises. Very frustrating when working on the assignments.
von David L•
28. Juni 2020
Good lectures. Programming assignments are useless fill-in-the-blank exercises, you don't really learn much from them.
von Thomas A•
10. Okt. 2019
The programming assignments really are like pulling teeth. There's not really enough guidance leading up to them.
24. Okt. 2018
The course videos and the programming assignments were lacking. And there was no support in the forums.
von Jeffrey S•
2. Juni 2018
Spent more time trying to work around a buggy grader than learning the underlying concepts.
von Frank T•
23. Okt. 2019
Too hard to understand compared to the previous coursed in this specification.
von Dipesh K•
13. Aug. 2022
Tough to comprehend. A little bit of written explanation might have helped.
von Hamid A•
13. Nov. 2020
Was very difficult. please add more expiation of mathematical equations.
18. Apr. 2020
Little unsatisfied with the final part of the specialization.
von Clashing P•
12. Sep. 2021
assignments are very hard and needs lots and lots of search
von Arsh K•
20. Aug. 2019
Lack of Keras training made it often hard to do layer code.
von Tom T•
9. Jan. 2020
This course needs more instruction on Keras.
von Mark N•
12. Feb. 2018
Poor explanation for alot of things
von Milica M•
10. Mai 2020
boring and uninformative
von João P B D•
4. Jan. 2019
von Martin B•
11. März 2018
von Alex L•
5. März 2018
I feel sad.
3. März 2019
von Selina M•
6. Aug. 2021
The course overall taught me new things, but I am still kinda unsure how to exactly use it.
The exercises and explanations weren't as enlightening as earlier and unfortunately left me rather confused, despite passing 100%. You definitely need to consult a lot of other sources for understanding the topic.
The last transformer exercise left me stunned though in how bad it was. When I understood something it contained obvious mathematical inconsistencies. It was the first time I needed the forum help, which is outside the coursera website and they force you to sign up in addition to coursera.
The tutor reacted fast but extremely patronising, going so far as pretending mistakes in the exercise didn't exist, but very eager to blame me for using an outdated version, that I wasn't using.
Did not enjoy the experience.
von Aldiyar K•
12. März 2021
Oversimplifying material, such as not showing any math foundations and proofs, does not lead to an intrinsic understanding of the material as well as fill-the-gap assignments do not enhance comprehension.
I understand that the course is intended for the broad audience but will one be able to implement those Keras and TensorFlow algorithms on a moderately complex problem, which is the ultimate goal of these courses? Highly doubt it because the code is pre-written for students and step-by-step guide is provided. In my opinion, one could go straight to assignments and induct / deduct the answers.