This course was not as good as the previous ones. The labs in particulary at the end are not visual enough. You train the model, have a good score, but we don't even try to test the model or visually see what it can do. Also most of the lab consists of running cells without requiring us to understand what is actually running. I had to ask chatgpt to explain me each lines of code to understand more deeply what the lab code where doing.

This course is supposed to have 5 modules, but I received my diploma after having achieved the first 4 modules. How come ? The video on pre-trained models alluded to much which was not explained. I believe this topic would have deserved a programming assignment.

Very light. The current material requires much less time to finish than annoucned at the beginning of the course. The teacher could have hence taken some time to go more into details, even though it's an introduction course

Course is too easy... And some guy copied my work for the final assignment after he reviewed it. IMO it should not be possible to review someone else's work, when you haven't passed the course yourself yet.

I feel the hands on lab should be taught and be apart of the videos in the course, I personally haven't been doing it because its all reading and not being explained, but overall the course is Good

Final submission via Mark failed because of technical problem. Last lab was crashing all the time after training the model, so I had to restart from scratch and lost quite some time in doing so.

The course was very elementary and brief but well organized. Week 4 (supervised and unsupervised models) is definitely too short to grasp the ideas behind the different designs.

The topic explanations are pretty rushed for beginners. The assignment has been unnecessarily added with lots of iterations that created issues with debugging and testing.

Extremely simplified course of ANNs, tells you how to create a simple ANN, but you are not going to learn almost anything about how it's components work together.

Good introductory course, just scratches the surface. What I did not like is that the instructor just reads the content for you. Could be improved.

It seems more a review of concepts that you need to have already have studied on other courses/books than a real introduction.

The voice in the video iss somehow robotic and some of the concepts are not explained well or at all.

These course is just for Introduction in Neural Network and Keras

Trainer was not so good

bad

Der Inhalt des Kurses ist sehr gut. Leider stürzt das Lab in diesem Kurs immer wieder ab, sodass man alle Vorgänge immer wiederholen muss von Grund auf. Das Abschlussprojekt konnte damit leider vorerst nicht beendet werden.

It's okay. Feels like an audio AI course. No personality, which detracts from learning. I didn't feel like I learned much from this course. This course has to be coupled with another resource in order to be useful.

Optional 10-15 mins lectures with more deep explanations and usage cases would be such an improvement.

There is not enough explanation and tutorial on harder material(as the course progressed).

not show conflict between keras jupyter and mac m2

subpar, spending all the this time finishing the certificate to have it say the non-credit cert, defeating the point

name is not correct

chaos

Good