Andrew is brilliant at explaining the fundamental concept, but the lagging thing was practical application, if you could take a real-world problem and code it along with the students it would become great.

Very well done in the substance. The "you don't need to know the detailed math"-statements might appear odd at times for mathematicians/statisticians, but are probably OK for a larger, non-STEM audience.

While I think this course is fantastic I really wish there was some place you cuold ask questions or engage in discussion. If I missed that then my apologies. Overall absolutely worth the time though.

Andrew ng is just fabulous!! however the optional labs must be worked upon since all those complex programming syntax and terms are pretty overwhelming especially if you are beginner to machine learning

I learned a lot in this part and would like to continue further but one point that I would like to raise is that it would be better if you can tell us about the in general function that are used in ML

amazing course and super easy to follow. my only problem is that it doesn't delve too deeply into the math and science of things and focuses more on practical applications rather than how things work

Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.

Content of the course is useful to understand all the important things about linear and logistic regression, like all theoretical concepts. Some codding video's needed to understand coding part.

I think some additional tutorial sessions explaining python code would have made the course even better . also concepts of vectorized logistic regression could have been covered in more detail.

By far the best course available on internet. It would have been a perfect 5 star if the jupyter notes didnt had functions imported from some other files, rather defined in the same notebook.

Simple and enjoyable learning experience, the only problem was that the content was too scattered without summarizing the lessons, which resulted in me not being able to connect all the dots.

Great teaching

Would have been better if arrays and vector operations in python are touched upon.

May be an option course to understand python arrays and vectors which are used in ML

Very good if you are new to machine learning. Highly recommended if you know nothing about the subject. However I would have like it more if projects were more engaging/challenging.

A very good start for machine learning journey. The optional labs were the main thing. Moreover we've to focus on self learning in this course. Especially for the libraries used.

Well taught, very beginer friendly. In my oppinion could have gone into more detail on some of the maths derivations for those who were interested as additional optional lessons.

All the fundamentals of ML are very clearly taught my the great Andrew NG & implemented in python in a algorithmic fasion to accomplish ML Operations & also to visualise them.

This was an excellent course that I would recommend to anyone. The only thing lacking is better dissection of the algorithms to their code equivalent within the optional labs.

It was an amazing course by an amazing instructor, but i wished if there was a full project that the instructor explain it step by step and how to apply the algorithm in it.

Theory Lectures were amazing! But, there are only 2 practice Labs. More variety of practice Labs should be included in this course. Other than that, everything was perfect!!

I AM GLAD TO TAKE THIS COURSE, AND IT CLEARS ALL MY FUNDAMENTAL DOUBTS REGARDING SUPERVISED LEARNING AND PROVIDES ME WITH IN-DEPTH KNOWLEDGE OF CORE CONCEPTS IN THE TOPICS.

Felt a little hand-holded. Good for beginners, and I definitely learnt a lot, but not an alternative to writing code and doing projects/competition on Kaggle by oneself.

Great course in Machine Learning for begineers, still required more details and topics which are required to be known for a begineer to get the solid understanding in ML

It was a good pleasure to learn algorithms from Sir Andrew Ng and stanford University. The Content in the course was very Easy and the concept were made crystal clear.

Andrew ng teaching was excellent. In my opinion, it is better if the exercises are harder and the number of topics covered in each section is Increased. thanks a lot

Good explanation of concepts. Assignments were straightforward for someone with modest Python experience. This first fragmetn of the original ML course felt short.