The class is good for persons who are new to Data Science and want a practical entry but does not go very deep into theory.

Week 4 was not explained as good as other. I still face the problem with the cocept of week 4. Rest everything is great.

Week 4 was somewhat disappointing, spent a lot of time in boilerplate codes. Was expecting to learn more about ML ideas.

Brilliant introduction to the topic sadly let down by bugs and errors in the Jupyter notebooks.

Still well worth taking.

The course in itself was great and the exercises were easy. But the sound quality in the videos should have been better

this lecture provides a good starting for learning Tensorflow.

there are good exercises with doing actual python coding,

Had some problems with the automated graders. I had to remove two JS cells from each exercise to get a correct grading.

It has more of keras and less of tensorflow. The course structure is good. A little knowledge of CNNS would be helpful.

Good intro to Neural Networks, but would recommend going through other Machine Learning courses if a complete beginner.

Some theories arent explained but overall, as a student, I obtained some experience on making a NN model by tensorflow

The content of this course is fantastic. The only reason for a four-star review is due to the troublesome auto-grader.

Always amazed at what coursera has to offer..if anything it has given me purpose as to what i want to pursue in future

Very easy to understand the contents especially using the high level API such as Keras. Very recommended for beginners

such a nice course to learn about tensorflow. i used these knowledge o enhance my technical skills as a ML programmer

Good course for beginners. Althoug best resuts will be for those who have come through Andrew Ng's inintial DL course

In general the course was nice. I just got some issues dealing with TF 1.x and 2.x. Anyway, I recommend this course.

I thought this course is more focused on the basic elements of TensorFlow, but it was very heavy on computer vision.

Very beginner friendly. Evaluation task could be a little more challenging than just copy-pasting the example code.

It is good, only it starts very basic and later assumes a lot of previous knowledge. But overall very informative.

I liked the course as it is practice oriented, but 4 weeks is too long for it. 2 weeks would be more than enought.

There are some issues with code in the graded Juypiter notebooks that keeps the grader from compiling submissions

Each chapter contains too less contents. Should compress the contents more so that it will be easier to navigate

No graded assignments, need more clarifications on how the params are calculated in model summary in tensorflow.

This is equivalent to two fast.ai lessons. It is a bit boring , but i guess one has to start with the basics

The course is a great recommendation for those interested in improving their AI, ML skills through tensorflow.