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

4.4
stars
1,560 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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151 - 175 of 342 Reviews for Deep Neural Networks with PyTorch

By Fabrizio D

•

Jul 30, 2020

Positive

-A lot of codes for practicing and learning

-The quizzes are short and focused

Negative

-The videos are too impersonal: it seems that the speaker is just reading the part, after a while I got tired of listening to him.

-Please review the texts: there are too many misspelled words

-Add more line of comments in the codes provided in lab

By Miele W

•

Feb 16, 2020

Well, as there are no sort of exams or real questions to answer in order to pass, it strictly depends on how much attention you put in following this course. IMHO if well studied, it gives you a solid foundation, in order to let you explore the pytorch module.

By Philippe G

•

Mar 10, 2020

Very interesting course. Gives a good introduction to pytorch. My only concern is the quality of the quizzes: It is often limited to 2 very simple questions. This does not allow you to validate that you had a good understanding of the said topic.

By Luca R

•

Mar 29, 2020

At the beginning, PyTorch framework seems very hard to understand. At the half of course you begin to have a clear vision of the problems. A negative point is the notebook for every topic. I would suggest one for week with everything inside.

By Eric

•

Jan 20, 2020

Good, thorough course. Does not hold the student to any kind of standard or accountability and quizzes are ridiculously easy to pass.

By Clara P

•

Jul 10, 2020

The amount of material was surprisingly extensive and the labs were very useful. The tests were not very good. The videos were OK.

By Andrey G

•

Jun 17, 2020

The quizzes are way too easy. The videos are OK (read by computer voice except one). The labs, on the other hand, a really nice.

By Vitalii S

•

Apr 15, 2020

Pros:

Good intro to PyTorch, great work.

Cons:

1) typos along the course.

2) lab is working too slow - better run locally.

By Paranjape A J

•

Feb 12, 2020

More graded coding assignments would have been better, but content is good!

By Simon P

•

Oct 17, 2020

The awful text-to-speech voice in the videos and the "We do this.... we do this... we do this..." information dump is poor from a didactic point of view.

The redeeming feature of the course are the labs, but like many of these little courses there's little encouragement to play around with the code.

By Olivier C

•

May 8, 2020

Useful if you are already comfortable with deep learning and you want to learn how to use the (great) pytorch package. If you want to learn about deep learning from scratch, the explanations are not very intuitive and skip over some very interesting features.

By Abdus S

•

May 5, 2020

This course provides a good amount of knowledge of PyTorch. However, the explanation and presentation are really bad. The monotonous voice and the quick changing of slides forces learners to watch the videos again and again.

By Geir D

•

Mar 8, 2020

Presenter is a synthesized computer voice. Slides and exercises are full of spelling errors. Contents is OK, but presentation is not very inspiring.

By Tom v H

•

Aug 27, 2023

Quizes are either way too easy, almost impossible to fail, or the questions are too unclearly phrased.

Another issue with the quizes is that a lot of them consist of only 2 (multiple choice) questions, with a necessary passing grade of 50%. So, essentially, you don't need to know a lot about the material to pass.

Regarding the classes, the concepts are explained extremely swiftly, leaving no time to think it through.

Also some random guy was hired to read the script of the videos, or perhaps they used text-to-speech software. So don't expect to be engaged much by the classes. They were extremely boring to watch. Overall it felt like the creator of this course just wanted to quickly churn out this thing and get it over with and receive that precious money. There's no love in it :(

Honestly not the quality I expect from a Coursera course that I pay good money for.

By Ryo S

•

Jan 8, 2023

If executed properly, this course should have been great, covering a good set of topics necessary to start working on DNN using PyTorch. Unfortunately, there are several issues that lowers the quality of this course.

Slides switch too fast after showing the last element, which is often an element or statement that is most important on the page. Too many typos on slides and notebooks. Labs often fail to launch due to a 500 error and when they do, notebooks often don't work due to outdated libraries. Most of the quizzes are too trivial that can be answered without understanding the important concepts covered in the videos (but some quiz answers are wrong as discussed in the forum; they are not fixed after years).

Personally I don't think it's worth $50 and so I've finished it in the first week before paying.

By Dr. C C

•

Mar 11, 2020

The general content of the course is good. However, I was experiencing a lot of problem accessing the lab platform. Also, there are typos and grammatical mistake everywhere in the quizzes. The audio of the video are done using computer generate voice over, instead of a real person speaking. I think the instructor of the course doesn't speak fluent English, which is understandable why computer voice over is used instead, but the non-stopping speech makes me a bit hard to concentrate sometimes.

By Ozan G

•

Jan 20, 2021

I hated the robotic sound in all of the lecture recordings. It made it impossible to stay focused. The homework was ridiculously easy (including the Honors assignment). In most of the quizzes, anyone from the street could answer correctly just by reading. The lab environment on the IBM cloud was really slow towards the end for training DNNs. I had to skip most of the labs before they finished executing.

By Martin P

•

May 12, 2021

The text to speech videos are not very motivating. There could be put more efford in the training notbooks and slides. Questions and assignments are too easy compared to the topics covered in the videos.

By Octavio L

•

Aug 28, 2020

Me resultó un tanto tedioso y demasiado largo. Se solapa con contenidos de otros cursos del certificado

By Hüseyin D K

•

Dec 27, 2020

Very short videos. Speaking so fast. It's like presenting not education.

By Aditya L

•

Aug 12, 2020

I had very high expectations for this course since it was offered by IBM and being taught by someone with excellent credentials. I completed the course material for the first 2 weeks and I found the lectures to me unmotivating, inadequately explained, and very clearly the lecturer read from a script. Important concepts were not explained neither the conceptual deep learning one nor the PyTorch programming ones. They were very briefly explained often with one short sentence. I thought the ungraded labs were very well designed but the lecture quality was so poor, it seemed I was just googling and learning 90% of PyTorch myself. I had expected quality from this course however, I did not get it so I decided not to pay the $50 subscription and canceled the course. I was disappointed since I did spend good 15-20 hours on this course.

By Tarun C

•

Apr 3, 2020

This course is a disorganized and unfocused. For example, much of the section on Bernoulli distribution is misleading or completely incorrect. It's also presented without context. Much of this is redundant give the other courses in this certificate program do a much better job of teaching ML concepts. The novelty of this course is about implementation using pytorch and most of the important details about how to use PyTorch and why certain parameters are used are glossed over.

Is this a course about ML and Neural Networks? Is this a course on PyTorch? It does both poorly.

Please see

https://www.coursera.org/mastertrack/instructional-design-illinois

for how to improve.

By Ulrich S

•

Dec 7, 2020

The course is extremely slow and low level. Some important information on the slides might be around for less than a second, whereas unimportant information might be repeated several times. There is too many quite similar labs and very few background information. The practice parts and even the final assignment are way too simple.

At least, it seems one is able to learn some basic notion of PyTorch,

By Alistair K

•

Jun 11, 2020

Utterly abysmal! The lecturer is clearly reading from a script an never actual explains or discusses anything.

The monotonous tone is surely a ML synthesis?

All of the usual typos and code bugs, however even worse than is the fact that some key slides only stay on screen for less than 1 second. A very poor effort on the lecturer's part.

By Timur U

•

Mar 29, 2020

Too many complicated theoretical materials and unclear practical instructions. I have lost motivation for this course.