Without having taken a Linear Algebra course previously, I thought the course was worthwhile to introduce topics. However, I had to spend ample time researching outside of the course IOT learn. In addition, although I was introduced to many LA topics, I still need additional practice in grasping certain concepts. This course is a good introduction to topics you'll have to research on your own.

It's a really good course with great tutors, really engaging and easy to follow. It can be very challenging at times if you don't come from a maths background. There are some assignments which are much harder than the examples in the lectures so some extra material to help you with those assignments would be great, otherwise personally they demotivated me. Other than that the course was good.

Having last taken linear algebra many years ago this course was a welcome refresher. Overall the course is excellent with clear explanations, good examples, and opportunities to practice your newly learned skills. That said the last assessment on eigenvectors did not evaluate learning and skills as much as reasoning about special cases and focused on problems better solved computationally.

The course is good as a refresher and it helps learning the intuition behind some concepts. The professors are very likable and do their best to explain the materials. However it is not good if you are looking for rigorous explanation of the mathematics as they go very quick on most of the concepts.

Taken this into account I would still recommend it to get some quick grasp on the intuitions.

I have experience with python numpy and pandas, so I found the assignments reasonable, but i think the programming assignments can be confusing to someone who has never coded before. There're a few times when I found myself lost in the instructor's explanation and needed to find more clarification online, but overall the videos are of great quality. It's a great course for self learning!

The biggest problem of this course is that dot-products are introduced before linear transfomations. I understood dot products through 3blue1brown videos and they are more intuitively explained as the product of the lengths of the projection and the vector projected onto. It is a subset of linear transformation a matrix vector multiplication where one of vectors is transposed.

I'm sad, because I finished the course, but instead of a solid understanding of linear algebra, I mostly feel confusion and frustration from what I was not able to ask the professors. But overall, the instructional videos are high quality, and the quizzes were challenging. At least it forced me to think critically about the subject, so I don't think it was a waste of my time.

The course generally is good. However I think there are some problems in this course: 1. The course pace is too fast, some concepts are hard to understand with few minutes lecture 2. The after-practice didn't help me to boost my understanding to the lecture. Even after I finished the practice, I still wonder why this happens 3. The final quiz has too much calculations.

I was expecting a lot from the course. But, it covers only the very basic portions. For example, I am not sure if I can start understanding the difficulties with normal equations and portions of linear algebra based on calculus. Also, it does not discuss parallelism of ML with linear algebra. I am not sure if this will help me read and understand Andrew Ng's ML papers.

The course content was spot-on, covering some of the most important basics for math in machine learning. I wish there were more programming exercise based assignments and less hand-calculation based quizzes to make it close to real world applications. Overall, loved this course and highly recommend it to data science enthusiasts taking baby steps towards deep learning.

This course has provided everything that it had promised. The professors of this course are really knowledgeable about the topics and the use of real life examples by them to explain each concept proves really helpful. Overall, this course would be a really good starting point for anyone willing to start their journey in the world of Machine Learning and Data Science.

Great course, but difficulty spikes after the first few weeks and problems become much more challenging, albeit far more interesting though. The course reaches its peak when it challenges you on the interesting problems presented to you during the last few weeks. You may need to have some basic understanding of algebra and a bit of calculus too before starting.

Really Good course for people having some basic linear algebra knowledge. They could have done better on explaining some concepts rather than rushing through it... But a great refresher course... One recommendation would be to suggest good books for Linear Algebra that might be helpful for students who take this course, some book which can accompany this course.

Really impressive.Thought if you are just starting maths after a time it will be little hard.Leacture material is very good,assessment were relevant,question quizzes build ur understanding,practical implications was most fun part for me.But again not recommended for someone who’s just starting would recommend 1blue3browns video series on linear algebra first.

Excellent Course Content and well presented. The instructors did a great Job in conveying the fine details . However The course should emphasize Python as a prerequisite and the instructors can include a lecture on "Basics on Linear Algebra with Python " in this course as the Assignments from Week3 through 5 involves applying Linear Algebra in Python

I feel like some part should've gone a bit more in depth. Due to time constraints for the course, I guess that's why some topics where not developed further. Would be quite nice in these cases if you could point to other sources, books, etc. Or maybe do a compilation of sources based on what the students have used to get unstuck on particular issues.

As paletras e numero de exercios foram muito bons. Porem o forum não é muito bom, existe questões abertas a 4 meses que ainda não foram respondidas, e muita repetição de duvidas.

Poderia ter apos os exercicios praticos, um video explicação de como resolver. Porque se a media é 80%, é presumivel que o aluno pode não saber alguma coisa e ainda passar

I loved doing this course. I did this course to revisit the concepts I have learned in my undergraduate, I remember most concepts but there are few moments where I have to watch videos again and again to follow along, anyone who is beginner might find it a bit intimidating, but don't give up just follow along and connect the dots between concepts.

I think this is a great review of linear algebra, especially for someone who has already previously studied the topics.

The example with the PageRank algorithm was very interesting and a great add to the course.

Possibly a downside of the course was a lack of practice of the material, especially considering how easy the notebook assignments are.

Goal is to get a gut feel through understanding math behind the python functions, but I wish they had start doing the code in parallel sooner. At end of the course, they accomplish this. Hand calculations in middle weeks were long enough to distract from the overview. It says its beginner course, but glad I had some background.

The course and the faculty were amazing altogether. All my queries regarding linear algebra were cleared and I began to look at linear algebra in a new eye.

The only flaw was inaccessibility to the correct Notebook link. Only after going through the forum was I able to get the correct link as it was, luckily, posted by someone.

Covers some good basics, but I feel that I would have struggled with the programming assignments if I didn't already have some practical experience with data science in Python and linear algebra. In particular, the last 20% of the course felt (eigensystems) felt rushed and could have been expanded upon a bit more thoroughly.

Good for starters. It gives a holistic view of linear Algebra. Geometric interpretation of Eigen Vectors was the highlight of the course for me as I wasn't aware of it before and the instructor helped me understand the concept very well! Thanks for putting forth this course and hope to see more in the forthcoming sessions :)

Overall, I thought this course was worth the time. Some of the material was challenging, but the instructors were pretty good at explaining clearly. Just a head's up: there is relatively little reading material here, so if you struggle to learn through videos you might have a hard time. That part was a challenge for me.

Could be nice to have the complete mathematical definitions given in an annex for those that are interested in refreshing their maths more than understanding the concepts broadly throughout the examples. Otherwise very well taught, I like that there are many examples where you have to get back to basic calculations.