Great Course

¡Buenísimo!

it was good

Excelente.

excellence

Excellent

tres bien

Excelente

perfect

great

good

good

good

good

Good

nice

Good

good

nice

ok

The course is good and has a nice mixture of theory and practice, which is essential for mastering complex concepts. However, I do have a few observations about the course quality:

- Several of the slides in the presentations and even the labs have a lot of grammar mistakes.

- The theory is often rushed in the lectures. The course would greatly benefit from a more careful analysis of the maths behind each concept.

-In its effort to make the concepts easier to grasp, the lectures keep using coloured boxes to replace mathematical terms. I found that to be more confusing, they use far too many colours and are too liberal with their use.

-Lastly, the labs completely broke down in the second half of the course. My understanding from the course staff is that an upgrade was made on the backend which did not go well and thus caused those issues. They should have several backup plans for those occurrences, starting with having the labs available for download so that the students can do them offline.

Overall I'm happy with the course and would cautiously recommend it, given the above shortcomings.

The course was fantastic for someone like me. I already knew all the math, and the course gave deep exposure to the needed Python routines and classes. The labs really help cement the knowledge.

Only drawback is that it went a bit too slow for me (NN with one input, NN with two inputs, NN with one output, NN with two outputs, etc.), but others might disagree.

I'm giving it a four because there were so many typos and mistakes (i.e. the gradient is perpendicular to countour lines, not parallel), lots of mispellings and wrong data on the slides and the speaker sounded like a computer (he pronounced the variable idx as "one-dx" - huh? I understand that there's going to be mistakes, but this is an one online course made for many people, and you'd expect that kind of stuff to be corrected over time since it is being repeatedly delivered.

But - it was a great course and I highly recommend taking it.

The content and its aplications are both amazing! Nonetheless it REALLY need some review! There are A LOT of grammar mistakes (missing characters, merged words, and so on), sometimes what is said on the videos is different from shown on the screen, there are lots os wrong questions on the quizes (the same question can be shown up two times with the exact same text and with two different answers each time). Some labs are missing code blocks ("Practice" parts with just the answer but it is not written what are we suposed to do... for example). I would like to thank IBM for the content, but it needs some improvement and THERE ARE LEARNERS COMPLAINING ABOUT THIS SAME ISSUE FROM YEARS AGO!

Despite the irritating computer voice and sloppy slides it is a good course. It is less a PyTorch course but an very nice introduction into ML and deep learning in general. Important concepts are introduced without overboarding the material with too much Math.

The labs could be more interesting and challenging. Towards the end the IBM Cloud was not working any more, before it was really convienent to do the labs in the browser. However, there are only a few requirements and anyone with a little Python experience can quickly setup a virtual environment. However, an instruction and a requirements.txt would be nice.

As with other IBM courses video materials, audio is AI generated. Only one video is human generated and it was no good. Video materials could be more thorough, as now they leave impression of going automatically from slide to slide. Reading materials are not good or non-existent. As for all ML courses in the series, going through foundational courses like the one from deeplearning.ai is strongly recommended. Labs are OK, explaining well some concepts, but could have been more challenging. Also, it would be nice to apply better coding practices and improve code reuse.