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The course is beginner friendly and provides an excellent starting point for anyone interested in machine learning. The content is well-structured, and the concepts are explained clearly with practical examples covering the essentials of regression and classification techniques. (The optional labs enhance the course by making coding more engaging and simpler). Professor Andrew Ng's teaching style is exceptional. He has a knack for breaking down complex topics into easily digestible lessons, making the learning process enjoyable and effective. I am also incredibly grateful for the financial aid, which made it possible for me to enroll in this course. Overall, I highly recommend this course to anyone looking to start their journey in machine learning. The combination of Professor Andrew Ng's excellent teaching, comprehensive content, and beginner-friendly approach makes it a standout learning experience.

Excellent course, it really lays the groundwork for understanding the concepts and some of the math behind it, and provides an opportunity to play with the python code in labs. This is a step up from "AI for Everybody", and a good prep for the Deep Learning Specialization. I'm a data analyst with some coding experience, prior coursework in calculus & linear algebra & basic statistics, and found this a great supplement as I'm also working through the Deep Learning Specialization.

Fantastic introduction to Machine Learning. The labs have been updated with widgets. You can add data points, change the polynomial order and many other changes that makes this a great way to understand how the different components of machine learning are done. Highly recommend.

This is a great Machine Learning course for the first-time learners offered by the best in the field. IMHO, the focus of course is on learning the underlying theories of machine learning rather than short-circuiting the basic concepts to the helpers libraries developed in Python.

Brilliant course! I really enjoy the journey and cannot wait to start the second course. It's such a great thing to have a course like this which is made with great endeavor. And spending time and thoughts on it is even more amazing. I am so lucky to encounter this course!

It helped me clarify many confusions I had, I am no longer left with doubts, I can now make my own models, and I am very grateful. Professor Andrew is very clear with the concepts, and I don't even know mathematics, but I know what I have to do :) thanks!!!

Perfect balance of application and theory, and wise choices in ramping up the complexity gradually. Discussion boards are very helpful, feels very much like personalized learning. Thank you!

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

Excellent course, very logical and well structured. Highly recommended to anyone interested in learning about this topic. Assignments are on the easy side but you learn a lot nonetheless.

This was a great course to understand all the math and logic that goes behind some of the most commonly used ML algorithms. Interesting and a great start to the specialization.

The course was brilliant and it presented very important ideas in a simple and easy to follow way. The depth and implications of the knowledge presented is quite profound.

Good for beginners. If you have taken the previous online course 'Machine Learning' taught by Prof. Andrew Ng, you may find this course much easier.

One of the best ML courses so far. The Course is well designed and very well presented by Andrew NG. I highly recommend it.

Precise explanation of the fundamentals of Machine learning techniques, using mathematical examples and python.

Very friendly for beginners, a good refresher if you already had the knowledge of machine learning.

- Amazing instructor

- Very clear and easy to understand examples

Great Great Great Course. Thank you for this amazing course

With all these jupyter-notebook labs its fantastic!

ilove how simple and rich this course is

very understandable

Very clear and intuitive explanation with a great instructor, though the contents are a little too easy, especially for people with a STEM background. More exercise could be set with less guidance (currently it's like writing ten lines of codes for every week of learning). Also, it would be nice if there could be an exercise dedicated to the use of packages like scikit-learn in depth, since that is what most people will end up using the most.

A very good introduction to Machine Learning. I would prefer some more math since this gives me more confidence in understanding, but the course is aimed to a wide audience so that's acceptable. I accompanied the course with Andrew Ng's notes on machine learning.

Andrew sir's teaching made the course interesting and exciting. However, the course was too easy and some more mathematically oriented discussions could have been done.

A good intro to ML. Strikes a good balance of the theoretical and practical aspects of Supervised ML.