The video content and theories went very how. However, week 3 assignment has some bugs and unclear explaination of compute_cost exercise.

Quite ok, but programming assignment was mostly copy-paste style. I am not able to repeat something similar independently after the course

A lot of great concepts covered in the lectures but only few were explored in the assignments. The assignments seemed fairly simple to me.

There were grading results that seemed wrong - I've submitted report on grading to explain details. Other than that, the course was great!

This course was nice for me.First Andrew Ng talks about mathematicall background of the concepts then you get hands on coding experience.

Good course. However expected some more mathematical proofs for some of the ideas like bias correction and exponential weighted averages.

Very good course. All the concepts explained very well. I just feel programming assignments were too easy, they could be a little tougher

It might help the academic learners if tutorials can be more engaging and rigorous than they are at present. But hey, not bad at all! :)

It's really great Mr/Andrew has a good way of explaining stuff even tho i need to search some stuff on youtube for greater understanding

I loved the course, as it provided concise explanations and covered all important topics required in Deep Learning. Thank you Andrew Ng!

Would have been 5 star but I found typos in the assignments and exercises -which have still not been corrected which is quite surprising

Good course overall . The batch normalization explanation were not so convincing. The last assignment on Tensor Flow need improvement.

The course is nice but the tensorflow exercise has a lot of functions that weren't explained before and implementing them was difficult

Its good hands-on course but to master it will certainly requires to dwell more into the specifics and need to work on various projects

Was a great course. Learnt conceptually and implemented Momentum,ADAM & rmsprop. Wish there were more exercises to explore TensorFlow .

I would have liked more programming exercises related to regularization and hyperparameter tuning, but TensorFlow was well introduced.

Weeks 1 and 2 were awesome. However I think we ned a more intensive programing assignment on Week 3 to get hands on with Tensor Flow.

I liked the course. I just think there should be more assignments. Perhaps after each week because the content is dense and complex.

Too much spoon feeding in the programming exercises, could have asked us to make a model with atleast x accuracy then left us alone.

This was the toughest course since lot of mathematical, especially statistics back ground is required. However, I could complete it.

The course includes lots of information and need focus and concentration.

The Tensorflow part is not enough to solve the assignment.

Its require basic python programming for implementation of neural networks , different models techniques to get perspective of it .

One of my best courses i have ever participated in, i gained a lot of knowledge and knew the underlying mathematics of every model.

Second step of the specialization,

a bit less rewarding than the fist course as more fine tuning and less overview of deep learning

Programming assignments could have been more challenging. Otherwise, the course instructor is pretty awesome!! Thank you Andrew Ng.