Its takes to long to train the models (6 hours each case). I was lucky because some students give me de advice to use google Free GPU to complete the each train in 2 minutes. Without the students tips It is impossible.

I suggest to add to this course information about to use either cuda with own local jupyter lab or either recommend some serice like googel colab to get better performance.

I guess the course was OK, but the complete limitations of the "provided" compiling environment is inexcusable. I tried five different emulators, eventually using Google's Colab tool in order to get any type of results within six hours. I don't know what you can do, but something needs to be done.

Also, I would recommend NOT having two different tracks (Keras & Pytorch). Because of the aforementioned coding issues, most of the real instruction occurs in the discussion forum. It is INCREDIBLY confusing when there are essentially two different assignments posting questions in the same space. Also, can you do something about all my "classmates" asking for people to review their work in the forum? In my opinion, that is NOT the purpose of the discussion forum. As the admins, can you please just delete those requests to make it easier to find the REAL discussions. You are smart computer scientists, can't you create an AI to filter all those posts into the bit-bucket?

Course opened late. One instructor did not prepare his materials and the exercises were not even accessible. I will not be purchasing from Coursera in the future because of this specialization course. Truly a huge waste of money.

But need to study extra as these topics are not taught like Transfer Learning

Most of this course is lab-work. However, the lab environment was inadequate. It kept crashing, disconnecting, or went to slow. While I understand that the Lab is a 3rd party tool, my payment was made to Coursera, hence they need to help ... at least by extending access for the lost time.

A very nice project based course to get hands on experience with deep learning

and transfer learning.

The Course is good, The labs were crashing which were causing lot of issues in completing the course

This is an excellent course if someone wants to learn transfer learning. However, having said that, there should be another task for which students should build their own model and compare its accuracy with the predefined one. With this, students would get insights as to how to build a deep learning model from scratch.

I got a chance to put what I learnt into practice and the idea of choosing between Keras Track or PyTorch Track was very beautiful. I can suggest another track for TensorFlow, making it a choice between choosing from 3 tracks instead. That would feel more complete.

Although my laptop's GPU wasn't up to par, I managed to run the labs and finished the project with a lot of patience . Recommended course for AI enthusiast, data analyst and role as an engineer in data science.

The capstone of the project was really good it helped me to understand the deep learning concepts clearly for providing the solution.

This course was easy to follow and understand. It gives you all the tools to complete it with ease

Putting in practice what I learned and experienced positive results was very satisfactory.

AI Capstone project was really Interesting. I learned a lot during project. Thanks Team

Very Good course. Learnt a lot from this course. Also got good hands-on experience.

I'm very happy with that

i am proud of my self when i study in here

thanks a lot

Excellent work from the teachers, thanks for your efforts.

Very good example to learn resnet pretrained models

Great hands-on work of everything learnt so far!

Please labs are not so good. Please improve it.

Thanks Dr. Alex, I always love your courses

Very interesting and helpful

Excellent course!

Marvelous course

awesome course