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.

very beneficial course i learned a LOT from it but i wish that there were videos to explain the the implementation side of the algorithms and equations in python

This course is great if you have a basic understanding of ml topics and want to go deeper into the theory or even if you want to know what actually is going on.

The course material was outstanding; however, I found assignments not challenging enough. I was literally tasked to add a few lines of code to an existing code.

Great course! Understood all the concepts and the fundamentals of ML but the lab sessions are a bit difficult to comprehend if you do not know python language.

Very informative and well taught course. Only reduction in stars is due to the quizes being too easy and not accurately testing your knowledge of the subject.

The Course is really good for theorical content, however I feel it might be lacking a little bit of practice.

The quizzes/ tests are really easy to pass, too.

Pretty useful, but I would have liked to seen more practice examples with actual code. I believe having someone to walk you through a lab is more beneficial.

I've understand the concept but here want add up on a lecture like how to implement those algorithm in python it will be easy to understand for a beginners

The course was pretty hard. But the quizzes in the middle of the videos rly helped. I would recommend a bit more help with the python aspect of the course.

The lab work should not be fully solved. Or program should be left with question, formula and method explanation. Answers could be given after submission.

very good course but it needs lab practice , it looks like we just run the code , aand if we want to write by our self it is hard . but thank you so much

Great introduction into machine learning, but I wish there were more options for practice rather than optional labs that are already completed for you.

This is a nice course. It gives a nice introduction to machine learning. The instructor is very nice at explaining concepts in easy to understand words.

The course is great and would have been much better if the optional labs had also been explained for a deeper understanding. Thank you for this course.