Some more practical examples can be included but the course material and topics and ecplaination were great.

Every concept was explained in a very easy and interesting way. Really liked the course and way of teaching.

I actually got the right course at right time and thank you to coursera for providing the course. Hats Off!!

Real life dataset use would have been more helpful.

Also, use of scikit-learn could have been explored more.

Good One, the course is to the point . Please include linear algebra as it was added in the older version .

I don't understand why the practice lab code for gradient descent and the lab assignment code is different.

Explained the complex concepts in very clear and simple way. Labs are very helpful and very well designed.

It get's exponetially harder as the weeks go by. This course could really use more programming excercises!

It would be better if we could get the downloaded notes of what the Mr. Andrew Ng is showing in the ppt.

A great course, very informative and easy to understand.

Wish there were more project based assignments.

great course. Dr Andrew ng explain very simple and perfect. but i wish it had more mathematical terms.

Weeks 1 and 2 were great. Week 3 got a little complicated and seemed a bit esoteric... But very happy.

It an introduction to ML. Course flow is fantastic and assignments are important to learn the content.

Awesome course. I wish the course were explained better though. Andrew Ng's teaching is just spot on!

It is a nice course , from this i learned what is regression and classifications in machine learning

Excellent teaching i thoroughly enjoyed learning and getting started with the machine learning field

I wish there were more practice tasks. But this course gives you good understanding of the concepts.

Best for learning deep concepts and mathematics inside but not sufficient for the job ready skills.

Loved the way instructor Andrew Ng delivered the concept. Practical knowledge can be poured more.

The labs are not very challenging, maybe some more coding would help to understand more material.

The derivations of some of the algorithms could have been covered, just for better understanding.

this course lacks a little bit in explaining the python implementation of the concepts taught.

The course teacher has the same tone all over the course hence makes me fall asleep and tired.

Really very easy to learn and the professor also explained the concepts from the basic level.

Useful introduction to Supervised Machine Learning, including Linear and Logistic Regression