One Word : Excellent.

I am unable to find appropriate words to express my vews about this course. This course is so well planned and well executed. The funadmental cocepts of machine learning and deep learning are explained in such a manner by Andrew Ng sir, that it feels like 'cake'. His style of teaching is so good that I sometimes feel that I already know a particular concept while I am learning it for the first time. Anyone... Anyone who is strugling to learn what are biases, what are weights, what the hell is this gradient? he should take this course imediately.

Highly recommended course. Take this course to start your mahcine learning journay with full confidence.

Terrific !!! This is an excellant course that give you in-depth intuition behind the famous regression and classification algorithms. Though most of these algorithms are now readily available in scikit learn, however it's better to understand them before using them blindly. This could also help you to reate an algorithm of your own.

None the less the exercise are good and the jupyter labs are exceptionals with interactive examples.

I would highly recommend this course specialization to anyone who wants to start their machine learning journey.

Respected Andrew Ng and his team are incredible. I am really grateful and learn a lot of good things from this course.

This course is well taught, its both an upgrade and downgrade to the old version of the course. Improvements are that you will be using Python rather than MATLAB/ Octave, smoother video quality and ease of understanding, with smaller bitesize chunks of videos that the longer videos in the old version with quizzes in between taught section rather than at the very end of a week. Only dwonside would be is that less mathematics is needed and doesn't go into the detail that the old course would have, however the course was designed for people with a less mathematical background. Honest;y loved the course so far and cannot wait to dive into the next two courses.

A+

The course is very well explained, there is nothing more difficult than to make very abstract concepts understandable to everyone and it must be said that thanks to this course, you are really armed to face the challenges that will come to you in ML; the course is fun, instutitf, clear, both very advanced but also very well explained, I recommend, to all aspiring ML enthusiasts or to those who would like to make a career in AI to follow this specialization! but also the others offered by DeepLearning. AI, thanks to the DeepLearning.AI team, special mention to Dr. Anderw Ng, not forgetting Eddy.

Thank you all for your dedication

Orson Typhanel Mengara

I started taking the NVIDIA track to learn how to set up the hardware. Although those courses were excellent, there were many gaps of knowledge that I didn't understand. After searching, this course hit bullseye - explaining all the concepts from the ground-up. I highly recommend this course as one of the first courses that any AI student take. It will make the AI journey much easier to understand. I've seen a lot of instructors and Dr. Andrew Ng and the curriculum developers behind the scenes are an amazing staff. It's rare to see such a refined and polished product. All I can say is 'thank you' and you offer an invaluable service to students.

I am currently a third of the way through the last course in the specialization. So far this course has made machine-learning concepts very comprehensible and easy to understand. Having been working in a student organization whose main focus is on AI, I felt as though I did not have adequate experience to help lead the organization. This course broke things down for me in a way that I needed. If machine-learning is of interest to you at all, I highly recommend this course as it will take you from a beginner who knows nothing at all, to someone who can hold their own in the world of ML. Thank you to the amazing team that put this course out there.

I have completed Supervised Machine Learning: Regression and Classification and in this course I learned plethora of topics and all 'ML' topics is covered regarding Supervised. On top of that, each algorithm is demonstrate very neatly through mathematical equation behind algorithms. Which help to assimilate the how each model is work and goal behind to develop to predicate the expected output. However, I face some difficulty to solve the assignments but by revisiting the lecture help me to score full grade in it. Now, I am so enthusiastic to complete the other two course of Machine Learning which is taking by "Andrew Ng" very nice lecturer.

The ourse design and way the instructor explains the subjects are perfect. I've graduated from high school this year and just know the basics of calculus, like some basic derivation rules, but it wasn't hard for me to follow the math and understand intution behind the math. Also, instructor points out how important it is to use parallel processing capabilities of modern computers and shows how to do that with numpy library and it's a really important best practice to code sustainable machine learning algorithms. I appreciate everyone who put an effort in this course, I'll definitely proceed with the second course of this specialization.

Participating in this course has been an absolutely wonderful experience. Andrew Ng's exceptional teaching style and approach made the complex world of machine learning remarkably accessible and comprehensible to me. His ability to break down intricate concepts into easily digestible components truly facilitated my understanding.

One of the most remarkable outcomes of this course was how it ignited a deep passion within me to continue delving further into this dynamic and fascinating field. Andrew Ng's guidance not only imparted knowledge but also inspired a genuine enthusiasm for exploring machine learning's boundless possibilities.

Fantastic content. One of the problems with other courses is that they don't teach any of the wisdom gained from years of experience. Andrew does. He teaches us what we need to know and avoids teaching what might be a red herring. The true value of an education might be measured by our ability to make better decisions. Andrew delivers on this, the most important outcome of a course. My only criticism is that some of the language used in the labs and assignments is misleading due to incorrect grammar. I spent far too long thinking that what I read meant the opposite of what was intended. This is infrequently a problem, though.

Professor Andrew Ng explained every topic from linear to logistic regression in such a clear and simple way that i could not help but smile at the fact that i was understanding everything that he was teaching. After completing the first week I felt as if i can contribute or solve any machine learning task. Word of advice, Spend time really understanding the concepts from the lectures and solving the assignmens will be much easier. The same way i couldn't way to log in every morning; i can't way to take the second course.

i can't believe i am limited to only give five stars! maybe like (5!)^100

Thank you so much!

Great course. I really enjoy how is goes more deeply into the mathematics compared to other ML courses. I also love the way Andrew teaches; he really makes you feel excited about ML. The one problem I have is that they use terms like 'fairly big', and 'works almost all of the time' when explaining some topics or in the quizzes. I understand why they are doing this as it is a beginner ML course, but as a Math major myself I think it is bad practice. ML falls under applied mathematics so I think the choice of words in the course should be more rigorous as this will prevent any confusion later on for a learner.

Firstly, all the materials in the learning sessions are consistently produced at a very high quality. All concepts are clearly explained, recapped in various videos, and reinforced through quizzes in the video and assessment labs. Furthermore, there are many honest advice to students about the real practice of machine learning. Moreover, there are many interactive lab exercises that 100% support learning and assessment. Finally, I also like the interview section between Andrew Ng and Fei Fei which gives valuable insight into career advice and machine learning research directions. Overall, 100% satisfaction.

The mathematics is explained in detail, it is true you don't need much mathematical knowledge, pre-calculus knowledge is just fine and helps with intuition, otherwise, you are taken care of with everything explained in detail. The quizzes are very helpful in checking whether you understood the concepts. I loved the labs because there was a lab for each section which gave me hands-on practice, seeing exactly what was going on and learning to apply the concepts. I am extremely grateful for the opportunity to have all this knowledge available to me across the world, this is a great course, and I loved it.

Course of exceptional level of explanation both in theory and from the point of view of labs that allow testing of theory with very useful practical examples. Thanks to Professor Ng for his ability to explain concepts that are not always easy, yet always with a positive disposition and attitude. The labs are extremely meaningful, especially if one gets used to solving problems on one's own, to understand where something might not have been understood. I finished the course with top marks in both the theory part and labs. Thanks to all the people who provided their skills and time to create this course.

The education given in the program was one of the rare moments in my life where I felt that I had really learned something. Although some things are offered optionally in this program, it progresses in a very comprehensive and instructive way. In addition, it is not only focused on completing the course, but also has a developer feature about machine learning. The library and tools that are not actively used in the course but used by today's engineers and researchers are also mentioned in the program. I would like to thank you for this effort, your high level of teaching and your kindness. Best wishes.

Exceptionally detailed and compact at the same time. After completing the course, I can confidently say that I am able to understand the basics of supervised learning completely, how to train a model and how to fine tune them. I had completed this course in 2017, and have started again inn 2023 to go through the course in python and know about the latest changes that have happened since the update to the course. But, this course has been made much better (it was already excellent at that time), and I cannot recommend it enough to all the people who had also completed the course before the update.

I recently completed the "Supervised Machine Learning: Regression and Classification" course on Coursera, and I can confidently say that it exceeded my expectations in every way. This course is an absolute gem for anyone looking to delve into the world of machine learning.

The course content is comprehensive, well-structured, and beautifully explained. From the fundamentals of regression and classification to more advanced topics, each concept is presented in a clear and concise manner. The practical examples and real-world applications make it easy to grasp even for someone new to the field.

Enrolling in this course was an exceptional decision. Instructor adeptly demystified complex concepts such as linear regression and logistic regression, providing an engaging and accessible learning experience. The practical labs, enhanced by insightful visualizations, solidified my understanding of these techniques. The course's well-structured quizzes and assignments offered valuable assessments of my progress. In essence, this course is an invaluable resource for anyone seeking a comprehensive understanding of supervised machine learning, making it highly recommended

One of the best online courses available is a course focused on mathematical concepts. This course stands out because it offers highly valuable practice classes in addition to comprehensive content. The course is designed to be accessible and easy to understand, using simple English to explain complex mathematical ideas. It provides a strong foundation in mathematical principles and offers practical applications to enhance learning. Overall, this course is highly recommended for individuals seeking to improve their mathematical skills in an online learning environment

This course did an excellent job of explaining the fundamental concepts behind these important techniques in machine learning. I learned a lot about how these algorithms work and their practical applications in real-world problems.For anyone looking to deepen their understanding of regression and classification, I highly recommend this course. It's a great way to gain a solid foundation in these important techniques, and I feel much more confident in my ability to use them effectively in my work. Thanks to Andrew Ng for offering such a great learning experience!

This is such a solid foundation for ML and AI that this course should be included in high school education (at least as an AP class). For someone who has not been close to solving math problems for over two decades, Andrew's articulation of the content with ease, made me recollect (forgotten long back) concepts that I learned during my pre-university and Engineering days. Will definitely continue with related content and strongly recommend this as a basis for any aspiring AI/ML engineer or people who wants to know - how the damn thing works behind the scene!

What's incredible about this course is that it focuses very narrowly on the most important building blocks of ML, which might almost seem trivial to many, but in fact can speed up your learning of more complex models since you get a chance to work out by hand each and every component of the cost function, loss function, gradient descent and finally the regularisation for both logistic and linear regression models. This course helps you build a very strong intuition for modeling and its at just the right level of complexity without any unnecessary details!

"I believe that it would be more effective to design tests and practice exercises that are challenging and complex. Just like how gold is highly valued because of its rarity and difficulty to obtain, the Certificate becomes more valuable and rewarding when we are faced with challenges that push us outside of our comfort zone. By providing more difficult tasks, we can encourage students to develop their problem-solving skills, critical thinking abilities, and resilience. Ultimately, this can help them to become better learners and more capable individuals."

This is a really good introduction to ML principles. With concise explanations of important ideas like logistic and linear regression, and overfitting, the course is designed to be easily understood by even the most inexperienced students. The theory is made easier to understand by using examples from everyday life and the entertaining teaching style of Andrew. Your comprehension is reinforced by the hands on exercises that use Jupyter notebooks and Python. For anyone wishing to begin working with machine learning, this course is excellent overall!