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

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?

Challenging!!

Thank you!

Thank a lot for creating this course. It really useful and practical for me.

This course was riddled with operational flaws regarding the image data, and how it operated in the IBM framework. At one point I was not able to run the labs with either PyTorch or Keras versions, and eventually just downloaded the notebooks and ran them in Google Colab to complete the specialization.

The data from the course is not well prepared, some invalid pictures in the data. And also sometimes the IBM platform can not run the training well, loss connection and need several hours of time for training the model...

This is a good enough project if it is your first Pytorch implementation. However, the program is unevenly difficult, with very few information for week3 assignment, and almost copy/paste assignment for week4.

The docker environment by IBM is horrible. I just got to finish my course running all the notebooks locally (except for those at the Watson environment)

Not well-prepared materials in Keras, especially in Week 3 (model-training) which took more than 3 hours to training and even not successfully.

Capstone project had delayed for a month, and after that the course resource also not ready.