Not man

Good

Super repetitive, same code is shown like in 5 videos, IMO not the right things are emphasized (e.g. it is mentioned in every video that you should use Tensorflow v2, but some new TensorFlow commands that you come acrosse are not even mentioned with a single word). The performance differences between different types of networks do not become apparent. Too mich time "wasted" on synthetic timeseries generation and non-deep-learning (statistical) analysis. No real hands-on (letting students copy-paste code that you have just seen in the lecture is a joke!)

I have done the initial Deep learning courses of Andrew, and they were very thorough and well explained. I was expecting the same quality, however, it was not so. Explanations were generally good, but the examples and the details around the architecture of the models were barely discussed or considered, besides pointing me to the next course (which I have done). I was a bit disappointed TBH, for an "applied" course I do not think this provides enough material to begin applying this knowledge into real life problems.

Really poor quality, sadly. The notebooks are full of errors, the quizzes are mostly coding questions instead of being about deeper understanding of the notions studied, and I don't think the videos are clear enough about what decisions are most important when building this type of model and how to make those decisions. Love the topic, but very disappointed, and don't think this is worth what I'm paying..

The course is merely a walk-through some Jupiter notebooks of Laurence. There are no proper slides with explanation of what's going on. I also don't see much activity from the course creators on the discussion forums. It is incredibly easy to complete the course without forming any deep understanding.

The weekly programming exercises are not even automatically checked for accuracy.

If you already have good knowledge of Neural Networks like CNN, RNN, LSTM, etc. then only opt for this one. Because they keep referring to previous courses in the specialisation for these. Also, they are only writing the code but never cleared about, what they are writing and why.

quiz's are pathetic! throughout the whole course the instructor talks about the advantages of RNN and LSTM and CNNs for time series prediction while not being able to prove this not even for one in the entire course, what a disappointment !

Me parece que no dan un buen enfoque a muchos puntos, los códigos no se explican bien, y abordan temas que son densos en minutos lo cual hace que quedes sin mucha información. No me parece que sea un buen curso por eso.

The course was not as detailed or in a flow like I expected from a deeplearning.ai course and the editing was also very bad, one thing was shown and something else was spoken.

A bit too high-level with lacking explanation on intuition. E.g. Conv1D was added to LSTM layers which helped reduce loss value, but did not go into the explanation of why.

Course is very quick and does not cover the topics in sufficient depth - explanations and discussion are all very brief.

Junk course. Andrew Ng is a great specialist but I'll never try courses from deeplearning.ai.

This course will be good only for very beginners. It's not deep and challenging enough.

To make it better you have to develop more challenging and GRADED! exercises

Poor audio quality.. Cant even hear in full volume

Very bad quizzes, no challenge whatsoever.

Too much repetition in the content.

It is a surface-level introduction

Could have been better

Too easy.

This specialization is false advertising. It does NOT prepare you for the Tensorflow certification exam. It’s especially disappointing after taking the fantastic specialization by Andrew Ng, and makes this specialization feel like a cheap cash grab by Coursera and DeepLearning.ai. This series of courses fails to prepare you for three reasons:

1 – The certification exam is done on whatever is the current version of Tensorflow (v2.6 as of writing). You can’t expect a specialization like this to update every minor release, but much of the coding is still on the v1.X version!

2 – The certification exam requires you to work in the PyCharm IDE. The IDE doesn’t even get a mention in this specialization and it is all done through Google Colab.

3 – The material is covered at a very superficial level. I was hoping to walk out of it feeling confident in using Tensorflow on novel problems, but I’ve barely learned anything about Tensorflow that I didn’t already get from Andrew Ng’s specialization. There’re a few minutes of lectures (some weeks less than 10 minutes). The programming assignments are either pathetically easy, or lack any guidance on what to do (seriously sometimes there’s no instructions at all, you have to guess what to do by the variable names), or both.

Save your time and money and go elsewhere to learn Tensorflow.

Even worse than the NLP course. Week 1~3 contains nearly no new material for tensorflow. It's just some replicated knowledge from previous courses. Studying synthetic data is good, but is off-topic for a tensorflow course. The course should focus on models and model structures for different types of time series data. My biggest complaint is that this course does not cover even the basic knowledge required by the tensorflow certificate exam (as advertised). Where is the multivariate time series forecasting? This is the most important part of the exam but the course totally neglects that.

Like the previous course, this is not a four-week course but a collection of short videos that can be watched in one morning. The first week (actually the first hour) provides interesting insights about time series but the rest of the weeks (hours) are a quick review of code snippets. The pace set by a sequence of one-minute videos is excruciating and makes it difficult to follow the lectures. In addition, there are no practical assignments, just some trivial quizzes.

I do hope that the deeplearning.ai team could spend more time polishing the materials instead of just throwing the Tensorflow docs/sample codes and going through them superficially. Please also change the instructor as I really doubt his professionalism/experiences in ML practices despite his titles. Please, please don't ruin your brand, deeplearning.ai. I wish to see more in-depth courses like the ones taught by Andrew.