Apr 30, 2020
An extremely good course for anyone starting to build deep learning models. I am very satisfied at the end of this course as i was able to code models easily using pytorch. Definitely recomended!!
May 16, 2020
This is not a bad course at all. One feedback, however, is making the quizzes longer, and adding difficult questions especially concept-based one in the quiz will be more rewarding and valuable.
von Zhenzhou Z•
Jul 01, 2020
It would be better to add a section explaining the experiment code of the famous paper.
von Ayush k•
Jul 06, 2020
incredible course covering from basics to a satisfaction level
von Farhad A•
Jun 16, 2020
It was well structured . Thank you
von Oscar A C B•
Jun 10, 2020
Excellent! Just what I needed.
von Marco C•
Mar 30, 2020
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.
von Peter P•
Jul 08, 2020
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.
von Julien P•
Jun 11, 2020
Here is a list of pros and cons:
Pros: great notebooks and many examples
Cons: the videos are a bit "cheap" (typos and artificial voice) and often miss the intuitions ("To do that, we code like this"). A bit light on the maths. Quizzes are too easy to validate (people may validate with a superficial understanding of what is going on).
Summary: The value of this class resides in the notebooks and in the time your are willing to invest in them.
von Farhad M•
Jun 24, 2020
I think it's a good course if you're coming in with the notion of deep learning pretty much clear and are more interested in learning the PyTorch syntax. I'm not sure how useful the course would be in terms of learning ML or DL from scratch. In particular the conceptual slides could be better.
The notebooks are well-prepared. Even though occasional bugs can be found, they aren't much to worry about.
von Felix H•
Jun 30, 2020
The course gave a decent and well-structured introduction to PyTorch. However, I would have hoped for less typos (including in the code on the slides), more challenging and instructive quizzes and real exercises (there are instructive labs, but the practice section is usually only a very slight modification of the already given code).
von Jesus G•
Jun 19, 2020
A nice landing on Pytorch and basic Deep Learning concepts. I liked the collection of code and practical examples. If only, I missed having more difficult practical assignments along the course.
von Theodore G•
Jan 11, 2020
Very intensive course. Could do more training labs. But this is definitely a very dense course. Extremely helpful to get started on ML/Deep Learning.
von Jian P•
May 10, 2020
Good introduction of PyTorch. There are some minor code errors and inconsistencies in the material but generally not difficult to figure it out.
von Mehrdad P•
Jun 24, 2020
The courses provides basic knowledge, but I wish that it was a bit more advanced and had more challenging assignments.
von Vitalii S•
Apr 15, 2020
Good intro to PyTorch, great work.
1) typos along the course.
2) lab is working too slow - better run locally.
von Patricio V•
May 31, 2020
Some of the courses are quite harsh, but finally come all togheter and there's a light at the end of the tunnel.
von Yanjie T•
Apr 05, 2020
the course is good, detailed, and practical, but the shortcoming is the lab quality, need to be imporved
von Krishna S B•
Dec 27, 2019
It would have been better if graded programming assignments were there.
von Youness E M•
Dec 21, 2019
There is a number of errors in the courses and in quiz
von Bilal G•
Mar 29, 2020
less one star due to the many errors I noticed in the
von harshita b•
May 18, 2020
good explanation with examples
von Roberto G•
Apr 12, 2020
very practical, lack of theory
von Lemikhov A•
Feb 19, 2020
No programming assingments
von Mohd N K•
May 14, 2020
von Richard B•
May 17, 2020
von Michael H•
Jun 21, 2020
This course was not to the same standard as some others I've taken on Coursera. I think the concepts would have been very hard to follow if I hadn't already taken the Deep Learning specialization, so it isn't a great conceptual introduction to Deep Learning. That said, it also doesn't deeply explore the nuances of the PyTorch library, or give very much guidance on best practices or how it differs from other popular frameworks like Keras/TensorFlow. The quiz questions are fairly shallow (and often frustratingly ambiguous). Probably the best part of the class are the ungraded lab assignments.