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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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1 - 25 of 342 Reviews for Deep Neural Networks with PyTorch

By Janis S

•

Mar 19, 2020

In general, this course is very useful and I have learned a lot.

But...

A large amount of information has been compressed in a short period of time. The synthesized speech runs too fast. Slides on videos also change too fast. Some of them appear less than a second. A learner has to pause or even rewind a video to catch and explore them for understanding.

Multiple errors in lab solutions (I would call them even bugs). Some of the proposed solutions do not follow requirements specified in preceding cells.

Wrong information in slides. For example, 'hidden layers' instead of 'neurons in the hidden layer' or 'hidden neurons'.

Too many spelling errors in videos, quizzes and descriptions apparently made by non-native English speakers. For example, two instead of too, ture instead of true, supper instead of super, rergresstion instead of regression etc.

Technical issues with labs appear too often - cannot start the server or unavailable at all for multiple days, broken conda installation due to outdated or incompatible module versions (in particular, torchvision and pillow).

I was expecting much more accuracy from a course led by IBM. An editor would be recommended to thoroughly review all the slides, quizzes and notebooks of this course.

By Prosenjit D

•

Dec 26, 2019

Horrible slides, instructor's monotonous voice, typos in exercises, and explanations are inadequate. Course is a rip off at 50 dollar a month.

By Michael X

•

Jan 7, 2020

Still a decent course but compared to other courses in this series, both the content and the

presentation of the content really lack clarity.

By Robson A

•

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.

By Henrik S

•

Dec 10, 2019

While the subject of this course is interesting, the general quality of the course materials is sub-standard of what I am used to on Coursera. I posted a question on the forum that the staff never bothered to answer. I used to a much better quality from Coursera.

By Jordan W

•

Dec 17, 2019

A terrific overview of PyTorch. I was especially amazed by the lab notebooks where the author went above and beyond to plot everything in a useful way. This allowed the student to visualize everything that was going on under the hood. In each notebook, there was also multiple ways of showing how to accomplish a task whether it be coding manually or using a PyTorch function to simplify. I appreciate seeing it both ways as it really demystifies the black box of Deep Learning libraries.

By lorenzo a

•

Apr 3, 2020

The main reasons i gave 5 starts:

1 There is simply a lot of content in this course

2 You can tell that the explanations were thought through and that reflects in the quality of the content

3 The labs are super helpful and presented in a very understandable way

Sure the course doens't cover some topics such as recursive neural networks, but you won't be disappointed unless you are looking for a very very technical course on NNs

By Ravi P B

•

May 17, 2020

A very excellent course to get introduced to PyTorch from bottom up.Also the lectures for Neural Networks and CNNs were short but really excellent and highly intuitive.These short lectures are an excellent way to learn concepts of Neural networks.Would have loved to see a week dedicated to sequence models.The instructors have really really done a fantastic job.

By Jeremiah J

•

Feb 20, 2020

It was a LONG course, very packed with info. But, I feel like I certainly learned a lot and have a great foundation for further learning.

By Daniel K

•

Nov 20, 2019

Amazing, really informative and helps a lot !!! really liked this course and would recommend this to anyone interested in Deep learning!

By Arct J Z

•

Mar 25, 2020

It is freeaaakin hard if you take the whole IBM AI ENGINEERING Professional Cert in the duration of a trial period.

By Yong S

•

Feb 3, 2020

Very well done course! The concepts are pretty clearly explained. Sometimes the labs have instructions that are a bit misleading but it's a very minor issue. I really enjoyed the instructor using colored blocks as a tool to explain codes!

By Cristina A G

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Feb 20, 2020

One of the best courses I've taken. Everything was really easy explained, step-by-step, with nice slides and lost of explanations. It is really clear and starts from the very beginning. I'll totally recommend it!

By shanmukha y

•

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!!

By Mohamed E

•

Mar 30, 2020

this course provides a very good and cohesive introduction to Neural Networks. I learned a lot during my journey and I recommend it for anyone interesting in the field.

By Aïssatou N

•

Mar 7, 2020

It was a very informative and interesting lecture. I learn a lot about the details when using PyTorch to build and train a deep neural network. I am so thankful.

By Shinhoo K

•

Nov 16, 2019

Awesome! This course gives me the basic workflow for using machine learning technique in my research! The materials in the form of Jupyter lab really help!

By Bằng P C

•

Feb 17, 2020

A good course for people who want to start with pytorch framework. This course start from sample problem to an complex ones help people understand easily.

By kenneth W

•

May 9, 2020

Excellent course is full of great information. A bit long. Since this is part of a series, some of the information is a bit repetitive.

By Nishant P

•

May 16, 2020

A very thorough introduction to Pytorch. The course is general enough to learn other frameworks like Tensorflow and Keras as well.

By Sreena R

•

May 21, 2020

Thanks a lot Mr.Joseph Santarcangelo for the wonderful sessions. I could follow all lessons. It was extremelly helpful

By konutek

•

Feb 1, 2020

Excellent Course. The Instructor put a lot of work into the content. Thank you for sharing the knowledge

By Mitchell L

•

Jul 15, 2020

This course had many flaws including that at the most basic it was riddled with errors, typos, and formatting issues.

Some more specific feedback is that this course seemed overly preoccupied with explaining math concepts or neural net architecture at a high level and glossing over much of the actual pyTorch specific programming.

The organization of the lectures make no sense, with separate lectures and labs for single class and multiclass versions of various models even though the functions all were built to handle multiple dimensions and so there was really no difference. Additionally because the lectures, lab, and quiz used all the same examples this means we would see the exact material presented over and over with no clear pedagogical reason.

Additionally the course seemed overly preoccupied with OOP to the point of replicating the functionality of several built in pyTorch classes obfuscating the actual material with no clear reason given for why we were creating our own version of extant classes.

Lastly, the quizes almost never asked any questions about pyTorch. Most of them were just the most basic questions about comprehending reading code. Things like "if input = 3 how many inputs are there?" or "which option is used for He initialization" and the options are like "He initialization or Xavier"

By Ankush K

•

Apr 30, 2020

Very good course only , complete the practical assignments they are important.

As for exam the question answers should be based on practical outputs, say make a model for

this dataset or so. Paste the result for the score.

By Surya P S e

•

Jul 27, 2020

Wonderful course!!! Best among all the courses under AI Engineer Certificate by IBM. Deep learning always haunted me with the maths involved but now I get a very good start with this.