Great course. If you would improve something I had a little hard time completing the test's because the code implementations were different to the ones seen in labs. the name of the varbiales changed and some thing's changed so I think this could be difficult for beginners

It was my first specialization which I completed from Coursera and it was worth my time. The knowledge shared by Andrew Ng is just incredible and I enjoyed the course a lot. Thank you Coursera for making such courses available for us and financial aid was also very useful.

One of the best Courses on the internet on ML, I am thankful to this course for existing. But if I had a single dislike was that, there was not much hands-on practical practice. Its more theoretical. I would have loved for Mr. Andrew NG to teach us code side by side too.

Great course for mathematical fundamentals of Machine Learning. However, I would like the optional labs (that introduce and describe the necessary Python code) to be better explained and walked through. It is hard for me to understand how the passage from concept to code

course is extremely awesome but there is just one problem that if this course can be audited for free, then there must be some option to mark it as completed without issuing any certification, so that it won't be a part of My Learning section as it irritates me somehow.

wonderful course, and this updated version is much better than the 2018 version which I took. The key thing I found is that I needed to know more Python to pass each weeks ending lab before you could go onto the next week lectures, so more Python knowledge is helpful.

Simply magnificent. The course does an excellent job in teaching the fundamentals of regression and classification. However, it would be amazing if the course went into more depth into some of the underlying principles used, such as MLE in logistic linear regression.

Very good, intuitive teaching.

I would have prefered if more teaching/videos were dedicated to the Python implementations and more rigorous explanations of the concepts. However, I'm satisfied with what I've learned as I feel as if I'm now able to apply the skills.

I feel the course is great but the lectures only focused on theoretical aspect,I believe adding few coding solving or error rectification lessons might increase the quality of course as just looking at optional labs and so the coding assignments felt too difficult

Andrew Ng is a great teacher. I took his original Octave-based Machine Learning class when it came out years ago. I've been waiting for the update in Python. I have to say, this class is not as hard or math-intensive as the original, but so far, it's been great.

A very interactive course that makes learning interesting. The Instructor has a warm disposition that puts the student at ease while keeping focused on the subject. The course would be enriched with the inclusion of interactive sessions or active student fora.

I really had a good experience learning new concepts of Machine Learning in this course, this course was containing all the necessary things such as thoretical knowledge, quiz's and practical knowledge in the form of optional labs and programming assignment.

Simply Marvelous, The theory presentation is very engaging although I feel that Lab assignments are not properly explained and sometimes it is not clear that what the statement demands. Discussions of Assignments can also be added so it is clear afterwards.

If they somehow managed to put thorough Practical hands-on hand-coding videos, it would be 5/5, but now it's a 4/5 just because I don't feel confident after completing the course. But since I got it from financial I don't have anything to complain about.

that was really great Understandable explanation , Use different tools for Showing diagram but one thing is really important to me was more project near industry of AI for getting more experience and this couldn't support that, but that's Ok thanks a lot

It is a great course to get you started on machine learning in minimum amount of time! At the end of only the first course of the series, I have developed a deep admiration for the potential that machine learning holds in my field of civil engineering!

My rating is not an indication of the content quality - Dr. Ngs work speaks for itself. However, Coursera's closed caption quality is so poor it is a borderline insult to those who rely on them to understand his content. Horrible captions all around.

Very nice course for learning. it would have been great if it had some coding practices also, like to have experience of coding it for beginners. This course much more looks lika a theory class. But anyways It was very very nice having this course

This is an exceptionally good course for beginners in machine learning. It covers all the introductory concepts really well and without losing any mathematical rigor. I would recommend it to anyone who wants to start out with machine learning.

Good or must say way better course than any other to start off with . I have been into Machine Learning from past 7 months but this course really helped me to understand the concepts and algorithms at more root and basic level than any other .

The content is good quality and very well explained, the course should encourage more effort from student to apply what is learned. I found most of practice labs too easy and in many cases zero effort required as everything was done already.

I find it absolutely wonderful. Any beginner can easily understand it.

I think one way to make it better is to add additional lab videos for doing optional lab stuff.

Enjoyed a lot, Andrew Ng you are greatest teacher I have ever met. Thank You.

The only negative mark I have is that I no longer have access to my code. There are many other applications that allow you access after you have taken the course. I don't like that I have to subscribe in order to use the code I'd written. :/

Great Course, It helped me gain a strong foundation and the content given in each of the labs and the practical implementations made the course most productive and interactive. Would've love more practical projects in the end of the course.