I​ really enjoyed this course. Although the video material was quite dificult to comprehend at times, it was sensibly put together in short video batches and also with many tests in between that really heped to digest and fully understand the material.

This was one of the best courses for linear algebra for a working professionals, students and researchers who want to brush up their skills as this course is very different from the regular book stuff.It was more practical with real world assignments.

Awesome course! Entertaining and digestible, with great assignments despite some hiccups in file organization and a slight lack of response from admins (understandable because the course is old). It was so awesome that I had to go and tweet the profs.

it's a very well structured and well taught course. The lecturers have the ability to keep the students interested in the subject and the various exercises at the end of each session are a very good way to find out where extra work/research is needed.

Clearly explained and key equations are derived with good step sizes. Quizzes and assignments are challenging (which is good!) and have high expectations for learners (which is really good for my motivation). Overall, I am really enjoying this course.

This course was perfect except for the last assignment. It took on average over double the time to complete (including for me), and I died multiple times :). Other than that the course helped me a lot with my understanding about matrices and vectors!

A really nice course, I had already done a Linear Algebra module in the university. But that was mostly mugging up and not knowing what this is used for. This course's geometric interpretation of all topics, helped me a lot and give a lot of insight.

The presentation an way of teaching is excellence; however, the course should add more reference or additional source or materials for more in dept detail for the person who feel that the simplified explanation in the course are still not sufficient.

This is a great course and the various concepts were lucidly explained by the course tutors: David Dye and Sam Cooper. I had the opportunity to understand the reasons behind most things that were memorized during my undergrad studies. Thanks a lot.

So exhausted, but amazed how the computer managed to process this kind of things for us everyday!

The lecturer were so nice and the explanation was so clear and funny too, although there are several assignments (which on my opinion) is sooo hard :((

Extremely helpful. I haven't taken a linear algebra class in almost 5 years and by going through these videos it helped me regain an intuition towards the subject. The videos do a good job of tying the material back to machine learning as a whole.

Great maths refresher content, with very useful 2D geometrics examples helping to build the intuition rather than just explaining the maths. I feel like I can understand this part of linear algebra now, and I know what to search for when I won't.

Great explanation of all the important things, with topical examples and practical tasks. Still, it seemed to me that the course was growing more and more complex exponentially by the end of it, so it was really hard to catch up starting week 4.

The perfect class to either get introduced to the important parts of Linear Algebra or to brush up your skills. I would definitely suggest anyone take this course for the quality of the lectures, the delivery, and the fun programming exercises!

Highly valuable introduction to linear algebra. Maybe the programming assignments are far too easy, while some of the quizzes definitely are hard. And the best part of the course was to introduce www.3blue1brown.com with it's videos on youtube.

A good mix of theory in videos, simpler practice problems to reinforce the learnings, and scalable applications in Python. Very much enjoyed the course and feel like I've learned a lot about linear algebra and the applications in data science.

I very much enjoyed the content of this class. The professor for the first 4 weeks was great! The professor for the 5th week seemed to move at a slightly faster pace with less in-depth instruction. His visual aids were pretty groovy though.

Excellent course for anyone who wants to know the nuances of Linear Algebra and its applications.The applications are not just mentioned,but one gets hands-on experience applying the concepts they learned,in code.Hats Off to the entire team!

The course is really helpful to those seeking clarity on the concepts. Week 4 and 5 really will really demand your attention. Loved every single bit of this course.

Would be glad if course would have included more visualisation to play with.

This is a good linear algebra course intro. May not be the one for who is looking for mathematical rigorous but it's enough for machine learning. Linear Algebra is important but not all topics and this course highlights the needed materials.

I needed a quick refresh of my prior knowledge of linear algebra for my MSc course and I wasnt disappointed. I also appreciated the complementary python exercises and the effort to put the material into a context of a real world application.

I got a lot of intuition about some fundamental aspects of linear algebra. Rest of courses on maths was very rigorous in terms of methods. This was more inclined towards applications in machine learning. I enjoyed the entire learning process

It was fun to work through the course. Sometimes it was challenging as it has to be. Now I have a much better understanding of the topic. Especially appreciated is the approach of the instructors to build intuition: it worked for me, thanks!

I have never visioned mathematics the way it was taught here. I believe every Engineer may he/she be a an ML engineer or not must take this course to just fall in love of mathematics. This course will inherently motivate you to dig deeper.

I really enjoyed taking this course. I could review and learn for the first time some important topics for machine learning, in special the eigenvalues and eigenvectors classes. I'd like to thank the course's professors and collaborators.