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It's a good overview. I think that to get a lot out of this course it would help to have at least encountered basic matrices, vectors etc before. It's not that these concepts aren't introduced it's just that I can imagine if you have never encountered these things before you might get overwhelmed a bit quickly. It would also help if you have some rudimentary knowledge of programming i.e. know basic syntax, what a for loop or a while loop is and other basics. I know a bit of programming and i'm pretty ok at math so the course was manageable for me. Especially good was showing how all of the concepts learnt can be applied to understanding the Google Page Rank algorithm.

The best part of this course is the conceptual overview it gives and the instructors constantly reiterate how this type of understanding is more important than just being able to chug through a whole lot of algebra. Computational skills aren't really that important because apart from very basic examples, a computer is pretty much necessary to do the calculations anyway and as we all know, just because you know how to plug stuff into a formula doesn't mean you have the faintest idea what you are actually doing!

I think a very bright person could probably fully understand this course coming at it from scratch but I know that I would have struggled if i'd never glanced at the math or done some basic programming before.

While this course helped me broaden my knowledge and understanding of Linear Algebra, I still won't give it a 5 star rating. And that's because I feel that the course doesn't match its content for its target audience. The graded assignments and the practice quizzes are way too hard for the content taught. More time needs to be given to each topic to justify the difficulty of the quizzes. Before taking up this course, I had been doing linear algebra for the past 3 years. And even I had to face some difficulties in clearing the graded quizzes. I can't imagine the plight of an absolute beginner. Nonetheless, for me personally, this course was a good refresher and strengthened my fundamental knowledge about linear algebra. Dr David was phenomenal in teaching the core concepts.

I would give this course 5 stars for the fact that in five weeks, the course is able to go through perhaps a semester or two or three of Linear Algebra (LA), and how LA fits into data science. I gave it four stars because I believe the program should include lots of links to reference and learning aid resources. Because I had done a couple other courses on LA relatively recently, some these arcane LA concepts were grasped with some, but not too much, effort.

If you are even just a little familiar with LA, this course will give you a good foundation for the LA relative to data science. So, if this is you, and you want to get into Machine Learning (ML) to understand how ML works internally, then jump right in.

Thanks to all who contributed to make this a great ride.

Despite having learnt about vectors and matrices in the past, I still find this course challenging at time due to incompleteness of lecture contents. But researching and thinking through these issues did help me better understand the course material. The instructors have a different view on teaching maths in the age of computers. Instead of focusing on solving equations, the main focus of the course is on building an intuitive understanding of the mathematical concepts. And they deliver on this promise. I also appreciate the effort to select only materials relevant to ML. This saves students lots of time and effort.

Overall, the course is good and well worth your time if you goal is to brush on Linear Algebra. It is pretty important that you have been exposed to linear algebra before though, as some topics are covered pretty quickly. My only complaint is that there was a lot of unnecessary obfuscation. The lectures constantly alluded to things without actually naming them (e.g., gradient descent in one of the earlier lectures). I found the "Essence of Linear Algebra" video series on YouTube to be invaluable to actually making sense of some of the lectures in this course, so if you do take this course I suggest doing the same!

The course provides an excellent opportunity to go through challenging problem sets, quizzes, and assignments. This not only boosts your critical thinking and problem-solving ability, but also instills resilience and fortitude - struggling through problem sets can be very arduous, but having the mentality to get through it is what the core of learning is. However, despite all these benefits, I would say the course instructors often rushed the concepts and had unclear explanations (perhaps I lacked the mathematical insight to see what they were saying, but I was often confused with what they said at times).

For purposes of learning (refreshing) linear algebra for machine learning, this course is a great tool. There were some blips here and there, where the explanations are lacking , but overall a good resource. i have to add that this combined with 3Blue1brown LA series provides optimal learning than the course alone. 3Blue1Brown provides better intuition while this course will walk you through the more rigorous math part of it. for best results ofcourse you may have to do solve lots of Text book problems yourself. (there is a recommended text book, but not necessary for passing grade or completing course)

Excellent course, give a fast and intuitive understanding of the concept that are below linear algebra. For people doing other kind of work, like phD in some other non-mathematical field, that somehow lack the mathematical back group I think is good place to start. Still need to see how those skill will test against the real world. But time wise is probably one of the best option. I also started with a book, Linear Algebra done right, but, even thou the concepts are way more deep in a book, I found that was taking me too much time to arrive at a reasonable understanding. So I opted for this course.

Actually I have learned linear algebra before but forget a lot, so I want to use this course to review it and help me prepare for the study of machine learning. As a computer science student(sophomore), I think the coding assignments are too easy for me. But it indeed introduce the core concept and equations in linear algebra, which are quite useful for future learning. In my opinion, freshman students or students just graduated from high school may feel more satisfied with this course. And it is better for students who have learned linear algebra before to find harder courses to learn.

Good course for your first step into machine learning. Very engaging. Great application with the PageRank problem. The course does dive into the core understandings of linear algebra and you do develop a sound mathematical intuition. The coding isn't very difficult and has been eased for non-programmers. However, what happened for a keen learner like myself is that I wrote code which I didn't understand very well myself, but still managed to get a full score. This made me a bit uneasy. Otherwise, an awesome course to get started on and it is possible to finish in two weeks.Enjoy!!

Excellent course to refresh linear algebra basics, build intuition and see the subject from a machine learning perspective. I wouldn't recommend it for people that are new to the subject, since the pace is fast, much is omitted and the assignments aren't always easy. Every now and then, the calculations come before the intuition, which can be tricky to follow. However, most of the course is very didactic and the combination of videos and challenges kept me motivated throughout.

I suggest the youtube channel of 3Blue1Brown whenever you feel lost with the subject at hand.

The lectures from the instructors were well-thought-out and planned, which gave it a clear line of reasoning and allowed them to give good examples. However, some parts of the content are glossed over, especially with the introduction to matrices. The instructor does not define what a matrix is and how basic operations with matrices work, though this is done when they introduce vectors. Overall, I would have liked a more rigorous and mathematical explanation of the content, but the course does do a good job of building an intuitive understanding of the topics.

The instructors explained the topics almost clearly. I would say the assignments were a bit difficult and did not have any explanations by instructors in the videos. More importantly, the support of instructors in the forums is very poor. Many people have had issues but there has not been any answer provided by the instructors. The submission of the assignments were a nightmare since grading of the coding gives a lot of issues even if the assignment is correctly done. With more support by the instructors in the discussion forums could be a much better course.

Overall great course. Explanations are good for the tasks given and assignments and coding labs are nice. As most users have already mentioned, there's a huge spike in difficulty in the first quiz of week 4. I personally found the last quiz of week 5 difficult too, but not as much as week 4. Sometimes lecturers make some mistakes on the board, but they are minor, and I dare say are a good thing, as they test you're critical thinking, I had much pleasure finding out I was right and that was a mistake on the board, and not in my understanding.

This was a really good refresher for material I learned long ago. The instructors were enthusiastic and engaging, and the production quality was good. The material is pretty abstract, however, and as with any brief course, it is difficult to develop a truly deep intuition about the subject without much further study and practice. I like that the homework was quantitative and required me to think carefully and practice the mechanics of doing the math. If nothing else, taking this course has me wanting to keep studying Linear Algebra!

This course provides a good overview of the basics of linear algebra for machine learning tasks. I recommend the class and I'm glad I took it, but it could be improved by adding more thorough explanations for quiz answers. This would have let me better understand how to arrive at the solution to a problem.

I didn't have any Python experience coming into the class and made it through OK, but there were times where this lack of knowledge interfered with my ability to complete the Python labs (particularly the last one).