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Learner Reviews & Feedback for Mathematics for Machine Learning: Linear Algebra by Imperial College London

10,061 ratings
2,026 reviews

About the Course

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

Top reviews

Sep 9, 2019

Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.

Mar 31, 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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451 - 475 of 2,032 Reviews for Mathematics for Machine Learning: Linear Algebra

By Rambabu Y

Jul 28, 2018

It is highly recommended. Very useful to those who are interested in AI and ML and looking for deep dive. Thanks very much coursera and imperial college London

By V A R

Jun 15, 2019

Brilliant course, thought intuitively and had a significant impact on my perspective in viewing transformation and other operations related to linear algebra.

By Zvinodashe M

Jul 26, 2018

Excellent course a little challenging but just the right pace and depth to get one back up to speed with linear algebra, looking to build from this foundation

By Harrison S

Sep 25, 2020

The last assignment (Page ranker) was really complicated. The jyupter platform also showed some issues. But the classes were really really good. I enjoyed it


Jun 21, 2020

This course gives you a solid base on linear algebra. The instructors are very good and the technique that is applied here to teach is unique and attractive.

By Nikhil J

Apr 27, 2020

Great intuition building. Absolutely enjoyed the course. I'm still a little bit behind getting the entire intuition, will come back and get it done. Love it!


Mar 31, 2020

Great Course to provide a better perspective to mathematics needed for machine learning. Really enjoyed the course and looking forward for more such courses.

By Kyle W

Dec 6, 2018

Excellent course. It's very practical - focuses on building your intuition of core concepts and applying those concepts through simple programming exercises.

By Gurunath G

Jul 8, 2020

Good course. Clears a lot of basics. It gave a different perspective of Matrices and transformations which I did not have earlier. Overall very good course.

By Anastasios P

Dec 22, 2019

Great course to get introductory knowledge and good foundation on linear algebra, especially Eigenvalues and Eigenvectors and some basic python programming.

By Flora

Jul 30, 2019

This course is amazing. Week 5 quiz is tricky but all the others are fine. The course might take longer than expected to complete but it's totally worth it.

By Sujeet B

Jun 19, 2019

Very good; contents covered gives an intuition of what's happening beneath the Mathematics. The lectures are interactive (which keeps your brain working).

By Biplab B

May 27, 2020

A very informative course that is focused on understanding the concepts of linear algebra and its applications rather than on solving numerical problems.

By Adelis N

May 11, 2020

The way this course is structured gives me confidence in myself and allows me to have a better exposure time towards the content. Fantastic way to learn!


Nov 5, 2019

The programming assignments are very well-designed. They are easily to follow and give me confidence to use Python deal with complex mathematic problems.

By Serge K

Nov 25, 2018

I love the stuff that I learned: the usefulness of eigenvalues and eigenvectors, coding pagerank algorithm, gram Schmidt to create orthonormal basis, ...

By Lee F

Sep 7, 2018

Enjoyed the course a lot! It stretched me at times, and I definitely got what I needed and know where to go to fill in any knowledge gaps in the future.

By Khaled A

Oct 3, 2020

If you are new to Machine Learning and mediocre in Mathematics (even though you studied this topic before), then this course is the right place for you!

By Tamanna U

Aug 11, 2020

Over the years, I have learned linear algebra from several sources but this by far enagaged me the most and taught me the intuition more than any other.

By Sumit N

Aug 1, 2020

Wonderful course, highly recommended for everyone who is trying to learn AI/ML/Data Science. Specially for someone who want to brush up their knowledge.

By Bohdan K V

Jul 20, 2020

The course was really good! If programming is better learned through books, math is better learned from courses where you can visually see all concepts.


Nov 8, 2019

A new way of looking at eigen values and vectors, every engineer should do this course.

It will help developing strong fundamentals for machine learning.

By Wookjae M

May 2, 2019

It was a "neat" lecture for understanding the basic of linear algebra. Programming assignments and test were well designed. Thank you for the lecturers.

By Gabriela S

Nov 3, 2019

Great approach, teaching the intuition of mathematics, this is exactly what I was looking for! Thank you to the amazing instructors for the fun course!

By Nuria C

Nov 3, 2020

Really well explained. I wish I had got such a professor when I learn these concepts in the highschool :) Lot's of examples and exercises to practice.