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.

Extremely shallow and sloppy made course. It is sad to see that the optimization done in the neural network is at the very least non-robust (if not totally random). The techniques used are simple illustrations that one can find better in youtube videos for free. The fact that people have to pay for this course is basically a scam, you should be ashamed of yourselves.

Maybe I had wrong expectations from this course. But to me it felt like the material in this course was extremely superficial. I was hoping to learn something, but it turned out to be a very basic overview of the material. Everything boiled down to "compile + fit" without the explanation of nuances associated with time-series settings.

The module on time series did not help at all in the certification exam. It's full of simplistic examples and broken links and optional assignments. All the while, the new iteration of the exam is more complicated and touches on topics not covered in this workshop on time series. Very disappointing.

The last two parts of this 'specialization' were pretty much useless. Here's some code, let's look at the code three times, let's take a kindergarten quiz, let's look at the same code again, here's the answer you can copy if you bother doing the exercise.

This is a quick introduction of using TensorFlow for prediction without any explanation for helping students understand the codes, the rationale, and the technical details we need to know for doing practice in daily work.

Gives a very shallow understanding. You can easily pass the quizzes without even needing to go through the colab code notebooks. This is unfortunately quite a good example of 'money can buy you a certificate'.

Extremely shallow ML course, with certain videos showing nothing more than running a few code snippets. More depth and explanation could go very far in improving the overall experiece

Really disappointment. Wonder what is purpose. After few videos it seemed like synthetic data is created just to create course. Lost interest very quickly

Extremely shallow. It's just to have an initial idea but not in depth.

To be honest course content was realy week.