There were many concepts which were totally new to me and many were known to me but I couldn't relate them with the machine learning problems now an I am able to do all those problems easily so thanks a lot Coursera and ICL team.

It is a good course on Linear Algebra. The teaching was excellent, all the assignments were challenging with some easy ones in the middle to boost your learning process, altogether I am happy to cover it with good understanding.

This course has great content and great way of teaching by instructors however the instructions in the programming exercises is not very clear. I hope the instructors take note of that. Overall, a fantastic Course content wise!

Being at an advance level of study, this course seems to easy to me but what I recommend is that any undergraduate or postgraduate student will definitely gain many interesting facts about linear algebra from this course.

It could be good to have more explanation about eigenvalues and eigenvectors because it is an important topic for data science. In general it is a very good course, you explained many topics in a simple and funny way.

I enjoyed learning in this course. There are a lot of different aspects that are covered here which is very interesting but I course is not for absolute beginners. It will be better if someone has a bit of background.

Nicely structured courses with enthusiastic teachers. Interactive enough to keep you thinking (which is key).

Some errors here and there and short moments of not enough explanation. But all in all an enjoyable course.

Great course to understand how linear algebra is related to machine learning. Focused on the concepts, and the concepts work rather than calculations. Would be easier if there was prior knowlodge of python and numpy.

This is a great course. The only thing is sometimes the calculations are hard to follow. I wonder if it is possible to let viewers click through a calculation process at their own pace. But the instructors are great!

excellent course to understand the linear algebra as a tool for problem solving in machine learrning though it not help directly but give you the strong understanding the fundamentals which will help in the future

Excellent course. I just wish the assignments were a little harder. The last assignment was the perfect toughness level. Made me connect concepts, look up stuff and actually get out of my comfort zone to learn.

The course did reflect the fundamental concepts in an excellent way. The only thing which frustrated me was " The PageRank" assignment and how was it even related to this course? Anyways, highly recommended.

I used to think that where are we going to use these matrices eigen values and vectors in real.. and I've got my answer from this course...Thanks to the professors who had given clear view on these topics...

Great instructors, excellent content. I would like to see more practical use cases of the material (at least as a self-study reading). And please add an explanation behind formulas for the eigenvectors part.

Fast paced linear Algebra, perfect to get refreshed. Might be too concise for those who learned Math not in English a few decades ago, will require to browse Forum for additional links to read on the side.

Great primer. Covers most of the important themes of LinAlg needed for applying machine learning, and also provides really good intuition. Useful for those wanting to sharpen up before further study of ML.

Good content, animated and visually-appealing lectures - considering it is mathematics, assignment material and quizzes are helpful for review, but minimal support and feedback for questions or problems.

It's a great course as a refresher, but for mostly folks with a lot of time. The assignments are fair, but sometimes it's dive-in kind of stuff, whereby the assignment itself is the instructive example.

An outstanding course which builds your mathematical intuition rather to prepare you for mathematical calculations. My opinion is that its contribution is significant in the pool of courses in coursera.

a bit rush course covering the most important part of linear algebra, give me a very good intuition other than mathematic notations! the course might be better to add some explaination on math side!

even though my code was right in the last assignment the grader kept getting timed out. it took 3 days to work and in the end the code was same. the course on the other hand was quite good and easy.

Great content and direction. Only negative is the sometimes frustrating experience with the Jupyter Notebooks: debugging what has gone wrong is very difficult, due to a lack of good error messages.

Be careful as a beginner in coding. It might be frustrating from time to time. I have spent the majority of my timing on the coding . At the end worthwhile, but did not feel that way at that time

Good, but sometimes it is neccessary to look for supporting materials. I took this course in combination with MIT course in LA and this offered another, more practice oriented, view on the topic.

The course is a great resource to brush up on the fundamentals of linear algebra and learn about the meaning behind the math.It prepares people for any further courses which use linear algebra.