The fundamentals of coding and machine learning concepts are taught in such a way that even a person with no background in computer science can grasp easily.

really interesting and helpful to fresh, however it's little bit easy for who have learned something about machine learning and the experiments are too easy.

Provides a good very basic but broad view of the subject. Lectures are really good, but lacks written material and programming assignments are way too basic.

Very interesting course as the start of something that will get more and more interesting. I am happy that I got this specialization and not only the course.

I found here all I need for first step in ML. Thank you. But Assignment you should make different. I mean varied tasks but not the same for each new attempt.

Everything is perfect except the library used which is turicreate is not as per current industry requirements, instead Pandas and Scikit learn can be used

Great course. Really loved the content. But would have been better if they would have released the last two courses. Basically a finishing touch is missing.

The course is a very good introduction to the specialization. It'd have been better if the course used an open source tool instead of a proprietary product.

A different version of graphlab was used without I think being duly noted, some functions work differently in newer versions. For the rest it was very good.

Effectively introduces to the basics of all different machine learning algorithms through case studies. The recommended tools are easy to use and understand

Really good overview and easy start into the machine learning community. Only point is, that they do not use the usual python packages for machine learning

Overall the course had a good mix of depth and breadth. There should be examples in the presentations and notebooks to help drive home the concepts better.

A great approach to get started with machine learning, focusing on the big picture first and then, delving into the intricacies in the subsequent courses.

Good course I'm just not a fan of graphlab because I think pandas is used more in industry, but the concepts and mini projects were great and challenging.

Really exciting and amazing. I liked the approach of starting with case studies, it makes the full understanding of the entire course easier and concrete.

Great overview of approaches in ML and large topics. Recommend to have python and some data analysis practice beforehand to get through material quickly.

Very good though a steep learning curve at the last lessons - inspiring lectures as well as practical cases :) Looking forward to the next ML courses :))

One of the assignments had wrong answers for some of the questions, which made passing it a bit tedious. Other than that, it was a fairly descent course.

Some of the links in this course no longer work and need to be updated. This does effect the assignments. Other than the links not working it was a good

Very good introduction to machine learning with good examples.

Some questions in the quiz could be rephrased to avoid multiple possible interpretations.

I like the GraphLab coding，and this course is an intro, not too much details, if you want to go further, better take the other courseras in this class.

This course is very useful for me as a ML beginner. The way they teach is very interesting and I can do some experiments at once. I like this course!

I enjoyed the course.

I wish it had more machine data driven models to to address more industrial type problems, for instance Predictive maintenance.

The course was OK, but I would introduce more about scikit-learn rather than a library that can only be installed in MacOS or Linux in an easier way

That's a good course overall, but the implementation is too much depend on graphlab. It would be nicer if the instructors switch to use scikit-learn