I think It's a great course to get your PyTorch fundamentals right; specially if one attempts/ completes all the codes themselves after going through the sections. (In some sections some contents are a little bit outdated, however considering how fast the field is moving, that's not unexpected or unfair in any way.) Some little added sections on the Parameter Efficient Fine Tuning techniques like LoRA etc. would have made this course more valuable. A brilliant course nevertheless.

This course fits me well and I gained lots of coding knowledge and practice in PyTorch implementations of ML, and DL. I learned a lot and feel great! Thank you, Bert Gollnick!

This is excellent course from beginner to expert level.

I didn't love this course. Overall, the topics covered are good. However, the code-along-videos are terribly hard to follow because of the use of VS Code to run notebook cells. This is exactly what a Jupyter notebook excels at so I don't understand why the author didn't use that. Trying to follow along with constant text/code completion windows popping up was a poor experience. I would have preferred to just have code discussions anyways. I don't need you to write every line, but I DO want to discuss each line in more detail. Why are we using this format vs. something else? What are the implications of coding something this way? Things like that are lacking in this course. Additionally, there are a lot of poor coding practices followed in these videos. For example, mixing imports, config variables, and other lines of code all throughout the files and using old, non-standard PyTorch code instead of the modern ways.

The course offers a valuable collection of code resources; however, the lectures lack detail and are not presented in clear language. Despite these drawbacks, I would still recommend the course for its practical code examples.