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Learner Reviews & Feedback for Deep Neural Networks with PyTorch by IBM

4.4
stars
1,561 ratings

About the Course

The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers. Then Convolutional Neural Networks and Transfer learning will be covered. Finally, several other Deep learning methods will be covered....

Top reviews

SY

Apr 29, 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!!

RA

May 15, 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.

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276 - 300 of 343 Reviews for Deep Neural Networks with PyTorch

By aditta d

•

Nov 4, 2021

Good lecture...

By Mohd N K

•

May 14, 2020

very practical

By Richard B

•

May 16, 2020

Challenging

By EC-231 V

•

May 19, 2023

mid

By Alexey K

•

Jan 28, 2023

The content of this course is actually quite good. Videos are clear. There is no material overload like in the Course 3 of this specialization.

The bad thing is the same as for all the previous courses: the absolute absence of any graded coding practice. All of the "shift+enter Labs" are hilariously inadequate to help retain anything you've learned during lectures. It's like learning PyTorch by watching how your neighbor is writing all of the code. A complete waste of time.

In addition, the quality of the quizzes has also degraded quite a bit when compared to the very previous course. The idea that anyone would be challenged by a quiz with only 2 questions, each with a multiple choice out of 2 potential answers, one of which is always nonsensical, is just laughable. Makes you wonder what kind of audience they made this course for, as the absolute majority of the quizzes are of this retarded type.

By Rafael B

•

Feb 11, 2022

The content of the course is interesting and light and allows for a good basic understanding of the topic. However, the presentation is not good. The automated narration in the videos is often weird and repetitive. The visual presentation is also not great, the colors and diagrams help very little with the understanding of what's happening in the routines (except for the skecthes of the neural networks themselves, which are pretty good). The lab notebooks are riddled with typos. The course would be improved by having a more detailed discussion of what's going on in the code before practice in the labs. Otherwise, I recommend the course for anyone who is starting in the field.

By Michael H

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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.

By Oleg G

•

Feb 4, 2024

Videos are sometimes too repetitive, e.g. when we move from 1 variable to many, or from 1 output to many, or from 1 hidden layer to many, all formulas and flows are repeated from scratch. Some parts are so briefly covered that they are too hard to understand if you didn't learn the context before (e.g. CNN). Too easy assignments (quizzes): 2-3 questions that often can be answered without watching the videos. Overall, if you are already familiar with deep learning, this course is a good overview over Pytorch API, although I think one could learn it much faster elsewhere.

By Gasm E M M

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Mar 14, 2021

I like to feel a human is teaching me, but I felt a robot is teaching instead. Also, many parts of the labs are copied from each other, and that's good, but the sentences and comments are forgotten unchanged and they don't belong to that lab. I preferred if the PowerPoints were designed better. Other than that, I can see that the author tried his best to include everything.

By Rajaseharan R

•

Nov 1, 2021

The presenter at times goes too fast and once he's finished talking the slide moves forward before there is time to absorb the material. The slides also contain errors. Should be more throughly reviewed. The labs also contain some bugs. The quizes contain some spelling mistakes and some of the quiz questions are unclear.

By Stephan W

•

Feb 6, 2021

Potentially a good course, but due to the very short videos and complete lack of supporting material (not even the slides of the videos), it's hard to follow. You need to watch the videos over and over again and take notes. Not sure why not even the lecture slides are provided.

By Julius W

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Mar 14, 2022

Very theoretical course. You can claim the badge without running any code. The additional honours course consisted of a total of 3 lines of code you had to write. I did not really enjoy this course. It covered a lot of things but was as dry as possible.

By Ahssad

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Aug 11, 2021

It is very fast paced. There are a lot of videos and not enough opportunities to actually reinforce what you have learned in terms of shorts projects. I think at the end of each week, there should be a small project in order to progress.

By Chaney O

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Jun 1, 2020

The lectures and quizzes are too short to provide much value. The material could be better condensed. The labs were useful, although at times, it felt like the same material from a prior video. In general, it was a good overview.

By Sabrina S

•

Mar 8, 2020

Ok walkthrought of pytorch, a lot of content but slight mismatch between rather basic DS topics and advanced programming skills. Materials need to be reviewed for spelling and grammar, some quiz questions are unclear.

By Yi M L

•

Oct 28, 2020

the content is definitely overloaded.. i am blowing.. felt like i went to college again. if cut some of the content it will be much more user friendly to learn.. for an online class prespective

By César A C

•

Jun 25, 2020

The course is quite complete, but it contains to many things already contained in the previous courses within the Specialization. The final honor part could have been much better.

By coursera s

•

Feb 2, 2024

The later labs had little or no practice exercises. The typos/mistakes in the materials were a distraction. It was disappointing to not have a fine tuning lab in the last week.

By Ben R

•

Jun 17, 2023

There were a few errors in the lessons (grammatical usually, occasionally more severe). All in all, I would recommend this course to others.

By Ferdinando R

•

Jan 20, 2023

Ok to show you how to use pytorch, but to learn ML you should really take the famous course everyone is talking about, it's much better.

By Massimo B

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Feb 23, 2022

quality of slides is quite bad and exercises are just a repetition of the class. Nevertheless the basic concepts are explained clearly

By William J

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Aug 22, 2022

good material but you should polish the voiceover and check for spelling/formatting mistakes - of which there are many

By Tony D

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Sep 8, 2020

Very slow and redundant material with previous courses of the "IBM AI Engineering Certificat Professionnel"

By Mutlu O

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Aug 4, 2020

More useful exmples in labs would be helpful to understand the possibilities with the method and tool

By Miroslav T

•

Jun 8, 2020

quality of videos at the beginning of course are low, fells like the machine is reading it