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!!
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 Oussama B•
Bad !!!!! Many mistakes, questions too easy !!! I am really disapointed
By Zaheer U R•
Amazing course with brilliant explanation
By Farhad A•
It was well structured . Thank you
By Krishna H•
By Ali A•
The labs are simply taking so much time. I am sure the is a better way to teach students than to make them wait 1 hour. Some people would want to run them locally, but this is not a solution, just a bypass. I learning a lot in this course and would reccomend. The best thing is that it taught me that CNNs are not super tough and with proper techniques can be handled.
By Fabrizio D•
-A lot of codes for practicing and learning
-The quizzes are short and focused
-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•
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•
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•
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.
Good, thorough course. Does not hold the student to any kind of standard or accountability and quizzes are ridiculously easy to pass.
By Mateo P•
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•
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•
Good intro to PyTorch, great work.
1) typos along the course.
2) lab is working too slow - better run locally.
By Paranjape A J•
More graded coding assignments would have been better, but content is good!
By Ben A•
Awful quality content that fails to teach or test you properly.
The videos are exceptionally poor using a text-to-speech narrator that makes you want to quit after only one video. Additionally, the quizzes are buggy with awful wording, typos, invisible options, and useless content. The biggest shame is that they don't use notebooks to test your learning with real examples that would reinforce both the theory & practical elements.
This course has no effort put into it & is clearly a money grab. Avoid this and instead try a deeplearning.ai or fast.ai course.
By Aditya L•
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•
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.
for how to improve.
By Christian T•
Lots of errors in the questions and answers, annoying content structure, bad videos (speed, cadence, auto-generated voice that consistently mis-pronounces things). Labs that are identical to the videos. No context setting or understanding beyond trivial mechanics.
Even worse, the quizzes contain typing/syntax errors that you have to ignore and then suddenly some of the quizzes contain errors that you must not ignore.
This is a ridiculuously bad course and I have no idea how it got to getting this many good ratings.
ABSOLUTE WASTE OF TIME. CHOOSE A DIFFERENT COURSE!
By Timur U•
Too many complicated theoretical materials and unclear practical instructions. I have lost motivation for this course.
By sada n•
it is too deep
By A A A•
This course is really good in explaining the concepts and pytorch. Everything was explained in a detailed way, well structured. However, I found the course too segmented. Some lectures, some quizzes, and some labs can be combined. Example for week 1, I think 1.1 (introduction to tensors), 1.2 (1d tensors) and 1.3 (2d tensors) can be combined to single lecture or all 3 lectures be one after another making it appear like it’s together. The 2 labs can be combined into a single notebook. The 2 quizzes can be combined into 1 quiz of maybe 5 or more questions. Similarly, 1.4 (Simple Datasets) and 1.5 (Datasets) can be combined, and so on. I also think that the honours content about batch normalization should be included as part of normal contents. Maybe more advanced concepts can be put up as honours contents.
By Анатолий М•
Курс "Deep Neural Networks with PyTorch" подходит для новичков, людей с базовым математическим аппаратом, с базовыми знаниями программирования Python и для тех, кого интересует математика нейронных сетей и машинного обучения. Курс делает упор на самостоятельность обучающихся и людей, которые сами заинтересованы в прохождении лабораторных работ. Здесь есть много инструментов для обучения, вычисления метрик, визуализации результатов, которые могут пригодится Вам в проектах. Курс прекрасно подходит для людей со средним знанием английского языка (материал разработан так, что он понятен и глазам, и ушам). Советую пройти данный курс на английском языке или с английскими субтитрами, чтобы погрузиться в изучение PyTorch и профессиональной терминологии разработчиков.
By Erdem Ş•
even with no mandatory peer graded assignment, for me it was the hardest course to learn in "IBM AI Engineering". So many topics and so many codes to check for each week. i liked it. i believe i will revisit the materials in the future.
By Georgios C•
Great introduction to deep learning with pytorch. It would help if the notebooks in the labs take shorter to run so that the students can experiment with the code and the models.
By Kartikey C•
In-depth course, goes in much more detail than the usual introductory courses, also emphasizes on practical hands on rather than theoretical knowledge