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

some of the modele and code is outdated.

good course

The content of the course is very interesting and highly informative, however there is a critical flaw in this course (at least for the keras library side of things), the problem is that IBM Cognitive Labs, the intended environment for the assignments, is incapable of running the later labs (week 3 + final) and will crash after 30+ minutes of waiting, this being due to the instructors having us use a relatively large database of images (~250 mb). Jupyter Notebooks on IBM Cognitive Lab struggles to just unzip the dataset (which is downloaded as a zip), not to even mention fitting the models to the data, which I found to be impossible to do with IBM Cognitive labs (for both week 3 and the final assignment). Ultimately I ended up having set up a jupyter lab environment on my own laptop, the problem is even then it took about 14 hours to fit the data to the models (in total, both week 3 and final assignment).

TL;DR the instructors have us using a pointlessly large dataset images which serves more to test our patience than our ability to create deep learning models.

Though this is the most interactive course of the certificate, the nature of the web host for training machine learning models likely prohibits many from actually being able to finish this course. I had to use Google Colab to train the models, as the IBM hosted site would take >10hours to train — in reality it would log you off before the model ever finished training. Due to this, most of the time was not spent on the projects, rather, they were spent re-configuring things to be run with a separate host. I've got degrees in CS so this wasn't a concern, but if you do not have prior experience in CS I would recommend taking a different certificate until this is fixed.

Very disappointing. The instructions are unclear in the assignments and it got frustrating choosing which platform to use to speed up the process and to bypass notebook errors. This was the least challenging and least interesting Capstone project I have done with IBM.

Please update the code since most of it is deprecated and some errors. Some code was also hard to work with since it could be better structured. The lab training takes time in any of the IBM platforms. I suggest working all labs in Colab.

Needs updated to reflect current changes that have been incorporated into the IBM platform. Instructions can be confusing. Assistance with the code is great but the course needs a once over update.

The information in this course is repeated over and over. You basically learn the same stuff, it could be cut in half.

the keras part was totally ignored

Learning content was good, but making assignments was a nigthmare, I could not set up an IBM Cloud account, becasue they could not verify my payment card, when i asked them to help me, they just responded "We have reviewed your account/transaction and will not be able to offer services. No further information will be disclosed regarding this matter. Any card authorizations will reverse within 24-72 hours depending on the issuing bank.". They ghosted me completely and did not want to help. I do not recommend. It's no wonder that with this kind of customer attitude IBM is far behind the competition today.

The code doesn't work with tensorflow 2