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.

Excellent course!! The training was thorough, concise, and taught in a manner that was easy to absorb. Andrew's friendly manner of teaching helps to make each aspect of the subject matter a bit softer around the edges than it might otherwise be.

I recently took this course and found it to be an excellent introduction to the fundamentals of supervised learning. The course is well-structured and provides a solid foundation for understanding key concepts and techniques in machine learning.

Explicit and intuitive explanation. The most incredible part is the setting of the corresponding jupyter notebook files which serve as both practical demonstrations and notes. I would give 5 stars to the course and keep going to the next course.

It help me understand some topics I was confused about, such as how backpropagation actually worked rather than just using it blindly . I also learned the importance of cost functions and choosing a good alpha parameter to find a local minimum.

Great introduction to prediction models using the mathematical formulas, plotting data and exercises to give you deep comprehension of basic concepts of machine learning. you will need just a basic knowledge of python sintaxe and data structure

Coming from a health science background, I found this course very useful as it was able to guide me through the basics with very lucid explanations and examples. Looking forward to completing the specialization and learning a lot of new things.

Beginner friendly, thank you for this course. I have a civil engineering background with no or very little programming knowledge and about ML and I never had to refer something outside of this course materials because of lack of understanding.

The explanations were simple and easy to learn, and optional labs were also very helpful in understanding the concepts studied during the course. Looking forward to further courses in this specialization and also deep learning spacialization🤓

I was searching for a practical and theorical course and this course has everything i wanted, the teacher is incredible good at submit clearly the information and complicated statements are explained in a manner that all people can understand.

Absolutely loved this course. I knew the basics of Machine Learning, so this part was a great reminder for me. Also, a big thumbs up for writing everything by hand - it let me understand gradient descent theory much more than imported library.

This course is great for beginner, but before learning anything on this course you must have some math knowledges about linear algebra and calculus in order to understand deeply about machine learning algorithms. Besides, everything is great.

This course is perfect for people wanting to get started with machine learning. The approach to the topics is clear and easy to understand and almost no prior knowledge in machine learning is needed. Highly recommended for complete beginners.

Very well structured theory and explanation, but the lab part is not very elaborative and easy to implement.

The codes are written u just have to run them and then later in the test, writing and implementing the code and logic gets difficult.

Prof. Andrew Ng is an amazing instructor with rich experience. I would like to be grateful to the entire team behind its realization. This course provides a balance between the theoretical aspect and the programming aspect. Highly recommended

The course covers detailed parts of explanations. Sir Andrew Ng and his team has developed this amazing course for learners. Algorithms are taught along with statistical content which can be hardly seen in teaching methods of any instructor.

I really happy for purchase of this course because I learn some of the important and fundamentals of machine learning. instructor tells difficult topics in very easy. I recommend this course for any person who want to learn machine learning.

Sometimes the magic of learning occurs when its the right teacher and the right subject taught in the right way, at the right time for you. This course was brilliantly put together, maximizing the chances of the magic of learning occurring.

Andrew explains with an amazing clarity. I absolutely recommend this as an introduction to machine learning. I appreciate that the course was focused in helping with the understanding of the topics, rather than with details of calculations.

It has a lot of mathematics, however grad to the way the course is structured it is possible to learn as course progressing and the coding part is well elaborate helping non-math guys like me to be able to learn and understand the concepts.

This is a course suitable for people who have basic coding experience and would like to go further to learn machine learning. The instructions from Andrew are very clear, every single material is useful.

Great thanks to Andrew and his team!

I really like the approach to learning that Coursera offers, this was my first course, but certainly not my last. The best part for me is the practical application of knowledge, which is done at the end of each chapter in the form of tasks.

This course is just awesome. Andrew Ng gives you the underlying intuition of the two most popular supervised learning algorithms, linear and logistic regression. I got to understand and implement the mathematical models of these algorithms.

It was very nice ! The concepts are very well explained and since I'm familiar with calculus and linear algebra I had no problems understanding. Most of my work was concentrated to learn Python, but the practical tests give a lot of hints.

This course helped me to understand the basics of regression and classification problem and laid a foundation for me to keep learning and exploring the Machine learning and AI field. Thanks to Coursera and Andrew NG for helping me to learn