Good

Nice

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good

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good

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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.