The professors are great at explaining and try to help you to think intuitively. However, you will still be expected to find out more about the concepts in great details on your own. This is the fun part where you get to really understand the concepts beyond the videos. The assignments were fairly challenging but extremely fun and useful for you to really understand the concepts. This course is relatively challenging and definitely not for the faint-hearted. Do try it!

It's SPLENDID!!! The courses covers all the relevant topics in very intuitive way, and gives a deep and concrete understanding of the underlying Linear Algebra topics !!!!

The assignments are designed in a way that it tests the skills in great way alongside giving opportunities to explore the dynamics and have fun !!!

It also teaches on programming skills by it's programming assignments and thus develops the overall skills needed to boost start any ML topic/ course !!!!!

Excellent course to get you to refresh or provide you with solid foundations of linear algebra, provided you supplement the course content with additional reading where you are either a bit "rusty" or completely new to a particular topic. I also find the quizzes and assignments particularly helpful in cementing your understanding of the material. Overall, I had a great experience and will strongly recommend this course to anyone on the quest to become a data scientist.

This is an excellent course as a refresher of the basic concepts in my college linear algebra. The instructors really put a lot of effort into making all the course materials. I enjoy the animations a lot! I am not a pro in Pandas but the programming assignments are actually very well-explained and perhaps a bit too easy. I'd thought they would put some plots and twists in the programming assignments. Very helpful course and great instructors. Thank you!

This course is excellent and it provided me a very good refresh about the linear algebra theory that I’ve learned in my graduate studies. The professor are great, the videos have an appropriate duration, and they help you build the intuition incrementally every week. The Python assignments are relative easy but they are of great value. I definitely recommend this course and I am looking forward to start the next course of the specialization.

A comprehensive course in Mathematics and Linear Algebra. If you're not related, or with rusted maths, don't be afraid, it will work for you, but it will demand some amount of time. A good time of course. Here I learned things I didn't fully understand. Great teachers. Some misses on explanations, will push you to Khan, tutorials, or books. Recommended course for everyone interested in getting in ML, AI, DS. A great introductory course.

Excellent course for those who like me struggle with intuition of math behind machine learning. This is not for beginners and it is not a general linear algebra course, it assumes that you have already a good grasp of the theory. The course for me took the theory I had and increased my level of understanding in how to apply it to machine learning. Also the videos are fantastic, I've never been so enthusiastic about doing math before :D

As a student of mathematics, I have read linear algebra in 2nd year in my university. But I keep finding the application of linear algebra. This course introduce a new way exploring linear algebra core topics. All the course video,practice quiz and assignment and graded quiz are excellent. Specially I like the Eigen theory problem and visualising matrices and vectors part. Thanks all the course instructor and Imperial college London.

Absolutely LOVING this course. Learning about vectors and matrices with simple examples of how they are used in ML is really slapping different to how I initially learnt about them 😍 (which was mostly in a theory bubble 🫧 ). The lecturer also explains things so clearly 😦 (high-key envious of that 😂 I no longer take that skill for granted 😩😬). If you're shopping for an intro to linear algebra, I recommend this course for sure :)

Before taking this course, I did some prerequisite self-study using Khan academy, and basic linear algebra text books to get familiar with basic concepts and the key terms. It really helped me to focus on the key messages in this course. I am amazed by how the instructor connects all the dots together and presents the dense materials in a succinct yet elegant way. It is one of the most rewarding courses I took in Coursera.

Very very excellent course on Linear Algebra by Imperial College of London :

I would like to thank @David Dye for teaching the intuition and essence of Linear Algebra.

Also @Sam Cooper, what a great teacher he is, couldn't wait to start the next course of the Specialization.

The best thing about this course is that whatever we learned, we applied all the stuffs side by side in ML.

Absolutely enjoyed the course. Thank You Coursera

Certainly the best online courseware I have attended. Prof. Dye breaks down most typical concepts of mathematics in simple and easy to understand blocks that makes this course fit for anyone. He brings out an interesting dimension to every concept that makes you comprehend it well and you're equipped to understand the practical applications of it. Would recommend to anyone looking brush their concepts of linear algebra.

This is such a great course for student already have background about college level linear algebra knowledge, but don't know the under relationship among those terminologies. For instance, after this course I finally know what is dot product means, what is eigen characteristics. The content of this course are well prepared, this is such a masterpiece from Imperial College London. Thanks to all stuff behind this course.

This course takes you through a beautiful journey that keeps you interested throughout. The professors have an engaging manner of teaching, keeping your appetetie healthy, and peppering the meaty concepts with good examples time and again for clarity.

Would definitely recommend this course to anyone who wants to develop enough understanding of Linear Algebra to do well with their understanding of Machine Learning.

The connection between machine learning ad vectors got clearer as the course moved ahead. The quizes are detailed and requires actual understanding of the concept which is not hard to grasp once you pay attention to the lecturers who themselves are so passionate about the subject, makes me excited to learn too. I can say, I finally, after leaving high school, have understood high school maths and it's applications.

This is excellent course on Linear Algebra. The best part of this course is, lectures focus on the physical interpretation of the topics rather than making you practice formulae without understanding. This course helped me refresh my Linear Algebra concepts and also helped me better understand change of basis and Eigen related concepts.

Many many thanks to professors for excellent course design and presentation.

No one can hate mathematics. The only reason you hate it or don't visualize it is because you never had an instructor who could do it. But, this course solves this problem with beautiful designed course content and intuitive quizzes that help you understand the underlying concepts on a broader perspective. Want to understand and visualize the basics of Linear Algebra used in ML, this is the course to apply to.

awesome content with excellent pace. no bullshit during lectures. only place for improvement would be to give relevant content in readings as the course feels just of videos and less reading materials for reference. Ofcourse ,one can look up in textbooks , but giving the reading materials in the course will improve the readability and findability and will be according to the lecture content. thanks for asking!

I took this course as a review for my data science curriculum. Previously, I was having trouble recalling the details of matrix arithmetic which was making it hard for me to get a deeper understanding of machine learning. After doing this course, you should have no trouble following along. For those already familiar with the material, it should take about 1-2 weeks to complete if working at a leisurely pace.

This is my first encounter with Linear Algebra and surely the course has been extremely helpful beginner-friendly. I recommend investing in practical mathematics courses as this specialization if you are new to machine learning field. You will be equipped with enough math background and should feel confident to enter more technical machine learning/deep learning courses.

A truly fundamental stepping stone!

This course is perfect for many including those, like myself, who haven't seen this for 20+ years. I can imagine that it would be helpful to have, at least, a proclivity towards programming if you do not have familiarity with a programming language (at least course comments tend to reflect this).

For those experienced with coding, no difficulty will be encountered, as focus here is trivial (numpy libs).

Just getting my feet wet in the genre of machine learning. This program gives excellent explanations and full breakdowns of the content it instructs on. The program also included real life examples in how this linear algebra can be used to answer problems. If you are looking to begin your AI machine learning journey, I think this course will get you started on the right foot for applicable mathematics.

This course has greatly improved my intuition in basic concepts of linear algebra. Through its comprehensive lessons and practical exercises, the Python assignments provided a very friendly introduction to programming, allowing me to apply the concepts I learned in a hands-on manner.

I highly recommend this course to anyone interested in developing a solid foundation in mathematics for machine learning.

This course is good for everyone, as rather than diving deep in the paper pen model, the intuition is taught. For those who already know Linear Algebra, it is best to take this course to understand, what you are writing and what each formulae is doing. For those who dont know anything about Linear Algebra, but is interested in Machine Learning, do this course to atleast have the intuition behind it.