The course material is excellent to learn the course's contents. Videos are very helpful for understanding. Assignments given in week#2 & 3 are really amazing for understanding coding in jupyter notebook.

We are very thankful for the teacher and others

It was the best course that I have ever passed. It was so practical and useful for me. My sincere gratitude goes to the instructor of this course professor Andrew NG and to Stanford university, Deep learning AI and Coursera for their financial support.

Thank you Andrew Ng sir and brilliant team of DeepLearning.AI , I have finished this course and start my interesting journey recently. I strongly recommend this new course in python which empowered by informative Lab and insightful visualization tools.

The teacher is really superb, makes the subject really simple to understand. Intuition chapters are specially helpful. Complexity adds up a little bit, but each layer is thoroughly explained.

Thank you Andrew Ng, and the team that made this possible!

Excellent first course on supervised Machine Learning. The explanations are very clear and the material, prepared by the instructor, is very didactical. I really enjoyed working on the notebooks and visualising regression and classification in action.

I am not new to python but new to machine learning and I feel like the course tought me a lot and also managed to simplify very complex subjects at the begining before stepping into details which it also does very well.

Andrew teaching is amazing ! .

Although most of this course was taught to me as a part of statistics course for my engineering degree, I appreciated how well the concepts were explained. This is a very good introduction for beginners to machine learning and regression in general.

Very good - I liked self-paced curriculum!'

Very nice lectures and well presented. Simplified enough, that I don't have to be a mathematician to follow the course.

Very good interaction with the labs to help me also see immediately the implementation!

The course starts from basic and inceases its level, the instructor taught smoothly and easy to understand by anyone, The course is having all the materials which you are needed while learning as ppt-slide, quiz, assignments and all are very useful.

As a mechatronics student interested in Machine Learning, I was very pleased with the course I took. Andrew Ng may be the best teacher I have ever listened to, he has an extraordinary teaching style. When he explains it, everything seems so simple.

I thoroughly enjoyed this course as a starting point for me in the field of machine learning. I still have a long pathway in my journey, so I will continue to follow the teachings of the great instructor, Andrew Ng. A big thanks to DeepLearning.AI.

Able to learn and co-relate all the concepts espicially I got to know why these many algorithms we need to predict something. I got to know about various real time use cases of these algorithms and now I am able to relate them with these examples

It's a really good start to understand better the neural networks later.

I saw a lot of courses about Machine Learning but was focused just on results (creating projects) rather than first understand very well what are you doing, like this course.

It is one of the most basic to start course with so easy and simple understanding of one of the most widely used machine learning algorithms. I would recommend this course to anybody who wants to start with basic and slowly diving into this field.

Amazing practical course. You get to see how those ML algorithms work under the hood. I believe I could never get such an easy intuition building explaination anywhere else. Huge thanks to professor Andrew Ng and his team for putting extra effort.

It is very interesting and useful course to gain understanding of Machine learning. I found it very useful to develop intuition of how ML algorithms work. Thank you so much Prof. Andrew Ng and Team for developing this course materials. I loved it.

Firstly i would like to thank Standford University for granting me financial aid for Supervised Machine Learning Course excellent and well oraganised weeks and all lectures were taught were clearly and even assingments were challenging as well .

Excellent course, a complex concept presented in a very motivating and simple way. Dr. Ny has the talent to keep you interested and curios for every concept included, is like a good movie that you want to watch from beginning to end.

Thanks Dr. Ny

This course is really structured very well and the concepts are explained in the best way possible by Mr.Andrew. The math behind the algorithms is explained very well and was easy to follow because of the practice labs after almost every lesson.

Andrew Ng has an amazing way of presenting the information and ideas relevant to machine learning! I took this course over my summer break, and I am glad I did, as I learned valuable skills such as the basics of linear and logistical regression!

This course is amazing! I'd been watching Andrew's previous specialization for a while and I really wished it was with Python instead of Octave. When I realized he - alongside his colleagues - was releasing a new course, I immediately signed up!

I like this course because you can actually impelement the theory you have learned in the lab using python.And also a very clear and enjoyable explanation by Andrew. I would recommend this course to any one who want to start in machine learning.

It's an absolutely amazingly designed and easy to understand course where there's enough information and materials to learn and utilize as the basics of machine learning. I can now say I'm very well versed in both linear and logistic regression.

This Course Designed for Beginers and also He explains the behind mathematics in simple way that makes me to understands the concepts and as well as the it works. in my point of view to start career ML go through is Course / Specializaton 😊😊😊

Great course, I had studied ML before in university but didn't understand the core concept and how does the functions really works under the hood, Andrew explained in an excellent way either the coding part or from mathematically implementation.