There could be more practice for module 4 and some more clarity for the problems(I did solve them, but took some time to figure out), but I loved the explanations and videos - I will gladly continue the specialization to learn multivariate calculus and PCA.

Course was very interesting but found some difficulties in the assignment section as it took almost hour to understand it. But, the course was very nice and also it help me to recollect all the mathematics part of Linear Algebra that I've studied earlier.

I am a computer scientist and this course served me to refresh all that concepts and exercises that I studied at the university, I only would ask to improve of the notebook's availabilty because sometimes I got disconnected and had to start all over again.

Multiplying 2x2 matrices by hand drives me crazy! Why instructors waste precious online time on that crap? Two, three matrix multiplications by hand during the lecture is perfectly OK with me, but why to do it over and over? The same with the exercises.

Good for beginner, but relatively easy if you have backgrounds in Linear Algebra. The course focus on making you adopt intuitions of how Linear Algebra is actually working geometrically which may be interesting if you only knows how the algebra works.

As someone with a bit of a background in linear algebra, this course is perfect in being a refresher to the said course. But unfortunately, especially for those who are completely new to the subject, the hurried explanations will leave some confused.

Great course, especially the first 4 weeks with David Dye. Unfortunately the lecturer in the 5th week is much harder to follow, and I needed to reference some additional youtube videos outside the course to get an intuitive grasp of the concepts.

Great lectures and wonderful scrutiny of matrices and vectors. Exploration of machine learning using Python, but the interface and project upload are somewhat kludgy. Stick with it and you can get the fundamentals even if the coding doesn't work.

it was a fantastic course it had increased my vision about a lot of things and had shown me the real power of linear algebra it was quit challenging and I wish there were more assignment for programing and implementing the mathematics in python

The course is very much beneficial, if you really want to explore the realm of machine learning, data science. This course provides basic in-depth understanding for the relevant topics of linear algebra that are crucial to machine learning.

The course was great for me. It opens up new perspective to some vector and matrix application. However, I must admit that you must have strong background with math before taking this course, as I was little bit struggling with matrix part.

It's by far the toughest course that I've done on Coursera. And at the same time the most rewarding upon completion. The course content is very applicable in the real world and it's definitely something that any ML specialist should know.

Great content, well explained, it's an overview of Linear Algebra relevant to Machine Learning, not a full blown course. Some of the assignments need clarity, especially the Python assignments. There is no faculty/staff to ask questions.

The lectures are excellent, but the scarcity of traditional math assignments prevented intuitive and reinforced learning. Thus the course should be considered a brief glance at linear algebra, rather than a proper course on the subject.

This Course takes you to the deep dive of Linear Algebra. But the lectures are not sufficient to solve assignments. We can make use of the resources given by Instructors for clear understanding of core concepts of Vectors and Matrices

The course is good to develop the intuition around linear algebra. However, some important concepts are not sufficiently developed to have a complete understanding of the course. I had to find other sources to complement this course.

The course overall is very good. The only drawback I felt was the lack of numerical examples to intepret complex linear algebra formulae. I would love to see videos carrying more worked examples of the formulae learnt in the course.

The pedagogy could use some reviewing, but the concepts and especially the reviews are generally laid out logically, and relatively easy to go through. Still recommend looking up things on the side through YouTube when you're stuck.

Some of the lectures are quite advanced for an entry level course. I had to go and research quite alot before being able to understand the concepts at times.

the lecturers are very engaging and I liked the use of practical examples

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.