The first three weeks' courses are a little too primary for me, while the last two weeks' courses bring some good insights with interesting examples. In a nutshell, this course is qualified as an introduction to the core of linear algebra and deserves a thumb-up!

This course is good for developing some intuition regarding vectors, matrix, eigenvectors. It would be very helpful if the final week had some more video lectures explaining things a bit more. The quiz is too tough if someone only base his study on the lectures.

some quiz were very easy to topic but some are were really hard i think there is a a little bit unbalanced questions in the course but they are effective too and i wish that i could watch or read solutions for this question because some are still complex for me

Excellent course and very practical; it's really focused on machine learning and there's the opportunity to learn some coding in Python. I would recommend it to everyone interested in machine learning. I give it 4 stars because there's always room to improve.

As I person who have 2 Masters Degrees in Law and Agriculture this course sometimes was to challenging. May be it's good reminder for those who have some strong math background, but you'll need to read and watch all lot of additional material in another case.

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.

it's teached by 2 teachers, I prefered the second one more, regardless I quite enjoyed how much exercises they put me through as I'm far more confident that I actually learned the discussed topics compared to tipical online courses

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