I thoroughly enjoyed this course. After using matrices and vectors for decades in my work, I have finally gained some intuition about what the dot-product operation, determinant and eigen-vectors actually represent. Thank you so much.

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

This course has provided me a better understanding of linear algebra concepts specifically on how eigenvalues, eigenvectors, matrices, and vectors can actually be observed or used in engineering (or even in day to day) applications.

It was a very good learning and I enjoyed a lot. Hoping to take the advanced level courses in Machine learning and related areas. Thank you very much Professors David dye, Samuel J Cooper and A Freddie Page. Hoping to see you again.

Awesome course!!! The course is very helpful for those who are willing to build an intuition of linear algebra. The coding assignments are a bit easy for CS students, but allow you to understand what has been taught in the course.

An excellent introduction to the core linear algebra concepts needed to understand ML. I especially enjoyed the emphasis on how matrices transform vectors. It provided me a much stronger intuition of the geometry than I had before.

Excellent. Exactly what I needed. A linear algebra course in machine learning. Top notch presentations, materials, and explanations. A nice blend of concepts and detailed calculations especially in transformations and eigenvectors.

I loved this course! Both Prof David Rye and Prof Sam Cooper were amazing and used brilliant techniques to ensure creative learning. I enjoyed the eigen vectors and values and pagerank algo module a little too much! Thanks a lot!

The course contains very creative introductions to some of the linear algebra theories that I was already familiar with. Could get new intuitions and better, deeper understanding of those concepts. Really glad I took this course.

I liked the course and huge number of exercises. Maybe my only problem is the academic form of the lectures that makes me lost sometimes and forces me to google for an Indian guy who can teach me the concept in a more easier way.

This course is little challenging if one has not revised Linear Algebra before, but quite interesting and fun given the examples and utility only after learning the basics of linear algebra elsewhere and then attempting this one.

Excellent introduction to Linear Algebra and its applications. Some programming assignments are tricky (Python based) but they are workable. The instructors are very effective in explaining complex concepts in reasonable terms.

This is an excellent refresher of vectors and linear algebra, and although I did it years ago in college I still found some new insights from doing this course. Its all explained very well without being bogged down in formailty.

Great course guys! I have done a course on Linear Algebra in my university and watched the 3Blue1Brown series on Essence on Linear Algebra. This course was a good recap of the concepts and their applications in machine learning

Excellent course. Material is explained thoroughly through concise short videos with plenty of visualizations that make linear algebra intuitive. Assignments are chosen carefully and the curated python labs are very enjoyable.

Nice course. This course is very good to build your fundamental knowledge for machine learning. This course gave me very clean and straight forward understand how mathematics play very important role in machine learning field.

Thank you for designing such a wonderful course. I find difficulty in understanding the concepts related to eigenvalue and eigenvectors and Page Rank. Otherwise, the other concepts have been beautifully explained. Thank you!

I really enjoyed the application of the abstract mathematical concept to real-world problems. This shift from conventional teaching of the subject makes one realise why math is at the core of all technological developments.

As for Chinese students, this course clearly explain the vectors, vector multiplication in a graph way, which for me is very useful, instead of in many Chinese university, which just state formula of calculating the vector.

I was very satisfied with the course. I'm really grateful for the effort they put into the programming exercises, so I finally began to put the theoretical knowledge into code. From now on I am able to experiment by myself.

Great pace and content very nicely curated. Loved it and will carry on with the specialisation. I am a professor myself and I am also learning a lot about good practices when it comes to teaching. Could not recommend more!

Love this course! Prof. David Dye is exceptionally great at explaining these concepts and the British accent also promotes my learning substantially. I'll definitely take the second course in the specialization very soon.

Excellent intuitive course in linear algebra. I had no idea how much I missed during my undergraduate studies. I think I went through this twice and might go through it once more. I would love another course by these two!

Great course. The instructor is really great (and neat), communicates the ideas really well and if Imperial College London is ranked that high worldwide, it's definitely because they hire professors this good. Thank you.

A really good course. If you go back when you need to you should understand everything in this course. If you want to visualize some of this stuff I recommend checking out 3blue1brown's linear algebra series on Youtube.