Overall I enjoyed the course, but it lacks structure. Some materials are assumed to be well known by the learner and surprisingly some easier ones are not. I like to see the math, but it needs more materials to support it. Most instructor's have very heavy accent and tend to speak too quickly, I find myself rewinding multiple times just to figure out what was being said. Homework's are not too difficult, and are enjoyable. Except for the last one where you need to wait for a peer review. I think this can be a flagship course with more efforts.

The explanation of TensorFlow is not enough and the programming homeworks have already a lot of already written (because, i would be very difficult to programming the all of the homework by ourselves in this stage of learning). I think it is better programming homeworks with examples more easy, but with more programming by ourselves.

At least, I think it is already well enough for the final evaluation, the automatic correction and then, the correction by peer only delay the evaluation.

I could not understand what the lecturer in the second week was saying. Overall good content but awful presentation. Exercises are ridiculous, my code is working fine, but since I do not use the same function as teachers and I do not get the same result to 0.00001, I cannot pass the class. Definitely will not be renewing this class. Think twice before signing up..I am sure the guys that made the class are really smart, and the content is high quality, but overall I am disappointed.

The quality of some of the video session is not good, especially for RNN's. Very general, badly explained and little practical information for the practical assignments. Yor have to "learn" the material, not just look for additional information, from other sources.

The pratical assignments are note always well designed, and some are full of flaws. After many many hours of dealing with some of them, you get the impression that you've passed the assignment but not learned much.

The Course is good, probably should be called introduction to advance deep learning, the complexity of the assignments make you put lots of efforts around them, that is rewarding at the end, make sure you have plenty of time to dedicate to this Course, one thing the Course could improve on is to try to minimize the switch between libraries and the low-level coding with high-level coding between TF and Keras sometimes it creates confusion.

Well, I think it's a good course for introducing us to Deep Learning and it has better(tougher) assignments than Andrew's. It also covers more knowledge than Andrew's. But the quality of the course is not that good. The Russian accent is not important because my native language is not English as well, but the assignments are frustrating. The mentors cannot answer the questions that widely appears in the course.

Sadly, this course leaves out a rigorous introduction to all the math behind Deep Learning. Also, it would have been nice to give an assignment to implement a conv net from scratch even if it is just a small one. Additionally the coding tasks felt like you only had to fill in coding related problems, like splitting text and setting up one-hot encodings. All the neural network fun was already prefilled.

I'd prefer a way more detailed explanation of different architectures and alghoritms + a more detailed explanation of Keras and TF. Programming assignments are more like quizzes where you don't write the code yourself, but rather fill in gaps, because during the course you don't study how to create a fully functional system from scratch.

Lecture slides need more written explanations, information, and math. Also, jupyter notebooks seriously lack information describing codes, explanation in neural network functionalities, and architectures. Please, practice clearer speech speaking, if it's hard to change, supply detail written notes to read for students.

I'm not sure that this course is needed at all. Folks are trying to explain multiple architectures of Neural Networks, without giving an actual understanding why it works. Plus I have a feeling that all of this things are going to explained in next courses of this specialization.

The Introduction to Deep Learning Course is a thorough and theoretically sound course. My concerns are that the Tensorflow code within the assignments must be changed to version 2 and that the quality of the instruction from the instructors is uneven.

Great course and materials. I'm glad that I'm learning a lot from this course. I don't bother with different English accents but a couple of lecturers having too many pauses really keeps me from focusing on the lecture.

Esta muy bien el curso en términos generales, pero para mi gusto falta explicación de algunos temas más en profundidad. Además, los videos de una semana en concreto cuesta seguirlos por el marcado acento hablando inglés

The video content is quite good and I've learned a lot. However, the preparation for the exercises is insufficient and the format of fill in the blanks is not really as educative as it is confusing.

there is some lecturers are not talking clearly stopping too much while explaining, the materials is very good with high quality

the pronunciation of the lecturer is not clear and too fast, hope they could speak slower and clearer

The introductory course is good. But I think you should include more reading material for RNN

Neural network introduction is conducted very chaotic. Not all topics are explained well.

先不说里面某位小哥嘎嘣儿脆的口音和销魂的语速。只说课程内容本身，首先有些讲义逻辑性太差，某些数学表达式有明显错误， 最后 作业里面的低级错误真的不应该犯。

not enough content in the video to pass the exam.

The RNN week was very bad.

各种口音的英文发音对母语为非英语的学生很困难

theory was good but at the time of Assignment i really felt blank as i have studied nothing, which i mean there is no technical support given in lectures, may be this is my fault that i cannot cop-up to the complexity. but still there is a room for improvement may be 5 to 10 min video to help student understand what they are supposed to do.

starting with coder decoder i literally gave up on assignment. so i had to search web and i felt lack of external matters too from where i could get help i am hoping that this response will the up coming student.

i focused on the things need to be improved but it does not mean that the course was not good over all. starting week was quite good i rate those week 5/5 stars. but later on the journey i had problem in understanding the pronunciation but than i realized its not that it is the material i am not clear of.

Thanks.

This is an extremely poorly prepared course in which the lecturers just throw material at you without bothering to make it even slightly comprehensible. One has to struggle really hard to understand what they are talking about -- they often use concepts and terms that have never been defined before, the slides are sloppy and often formulas make no sense. That said, I'll probably continue struggling with the lectures, since this is (unfortunately) the only advanced resource for deep learning at the moment. I really hope the lecturers will listen to the multitude of negative reviews and make an effort to improve their presentation.

good course with great lectures , but the assignments are very painful to complete , they are not hard but the training of the model takes to much time and the coursera notebook always crushes , it took me 1 week to finish an assignment after several trials of training the modal , i ended up by using google Colab with accelerated GPU in order to finish the assignments, also the instructions in the assignments are often not very clear. i suggest to reformulate the assignments and delete or modify the part where you have to train the model and wait several hours to submit the notebook .