The final project was missing some prompts for additional code. I'm all for research but there should be a heads up that we won't have all the prompts we need, since all the tests before specifically asked for the code needed to pass.

Maybe a bit repetitive, when you just finished Course 1. We see a lot of lines of codes explained again from course 1 and I think that could be avoided.

However, the new concepts are nicely introduced and very interesting to implement!

Sudden spike of difficulty and approach in the final assignment, but overall, the pacing is really nice. You really can't solve the last assignment without reading the discussion forum or looking for things for yourself though.

It was good, but similar to other learners I feel a little light in content. Though in tandem with the deep learning specialization gives a good view on convolutional neural networks as well as its implementation in tensorflow.

I wouldn't say that I learned a lot more than from the 1st course (Intro to Tensorflow). I would also have appreciated a deeper dive into the theory of CNNs, because otherwise the programming assignments turn into a copy-pase

Loved the course. I would have liked a module on saving your own models and then loading them later. The Inception one is nice, but it comes with some "niceties" that I don't think you have with loading a home grown model.

It's an great course with simple explanations about the Deep Learning topic. It's a perfect fit for beginners or those who want to have a practical review before starting using Tensorflow 2.0 with keras implemetations.

It was a great course but there wasn't much theory into explaining why and what's happening. A course to get started with the coding without actually needing to require what is happening in the background.

A great course for those who want to start building their AI models using Tensorflow. It explains how to use the required tools for different purposes like data augmentation, transfer learning, etc.

Nice course. Even though I have previously done some projects using CNN and multi-class classification still this course let me to have an insight to how these APIs work. Keep Up The Good Work!!!!!!

This course awesome, but the notebook from coursera "i think" doesn't support any experiment we want, so we have to do it on google colab. But great, limitation is okay as long it's still graded

The course is really nice. But would be better if the convolutional layers were a bit more detailed. It was a bit difficult for me to understand all the parameters e.g: input/output filter size.

The course was fine sometimes I feel too easy. I would like to see more of the available options for the layers, such as padding, stride. filter size, mean average, batch normalization, etc...

Good one for understanding convulutional networks. But the last assignment is not good. No explanation and you need to change the code provided to finish it. What they say you should not do.

Assignments are good, but it should concentrate more on the actual problem rather than the file reading or any nitty gritty details without any hint. Thanks , this course is good in overall.

Great course to learn newer aspects of TF. For me a great revision of ConvNets and a confidence builder. If there's one thing I'd fix, it would be the autograder and how often it crashes.

I liked this course, and also the way progression is taking place but the time required to complete this course needs to be reevaluated. This course can be finished in 8-10 hours easily.

Found the hands-on not very interesting. Couple of them focussed on file handling and stuff rather than on more important stuff that getting into the hoods of transfer learning, etc.

I think this was a good course but the standard of exercises and quizzes was too easy. More conceptual questions especially in quizzes would help in understanding the topic better

Overall good. Could have gone in bit more depth on how various hyper parameter tuning and regularization methods impact the model training. Provide some best practices tips .

the last exercise needed a big upload, made it imposible (for me) to do. This was a problem not related to the subject, should use data downloadable directly from internet.

Most of the Programming Assignments are a copy-paste routine from colab notebooks provided

the last one was pretty challenging though ^_^

(Im experienced in Programming)

This course only requires few hours of work and I would like to see more depth. The parts on image augmentation and transfer learning were pretty interesting though!

Curso muito legal, a única coisa que ficou um pouco abaixo do esperado foi o último exercício da quarta semana, não foi construído com o cuidado visto nos outros.

The assignments are not challenging enough. The concepts are really well explained and for someone with no background in this area, this is a great learning asset