The videos were well structured, but the quiz sometimes were far more difficult than the practice questions in video. I had posted on forum but no comment nor reply. Quiz answers were not elaborate enough to understand after making mistakes. So I had to ask my father who's extremely good at maths many times, for explanations. Without hi help I might not have been able to understand as well. Need improvement.

Cette formation m'a permis de comprendre beaucoup de chose , en particulier les valeurs propres, les vecteurs propres , l'alebre lineaire ! Mais je veux me perfectionner professionnelement dans le domaine de la datascience , malheureseument je n'ai pas de moyen pour payer une telle formation . Je sollicite une aide financiere aupres de vous afin de me permettre a trouver une telle opportunite !

This class fluctuates between impossibly hard, because a lack of instruction and examples were provided and too simple, because the same question is asked repeatedly. There is also very little mention of machine learning, despite the name of the specialization/course. That said, it was still the best survey course of the linear algebra concepts most relevant to machine learning.

The course starts off well enough, but by week 4 the intuition for certain concepts is not imparted well at all, and the correspondence between notation from the lectures and that used in the practice quizzes breaks down badly.

I gave it 3 stars instead of 2 stars because the geometric intuition that is imparted is quite good, even though at times the notation is sloppy!

Let down by final test on page problem. Just not covered well in the lecture in order to make the inuitions needed to answer the questions fully. Test interaction pretty annoying. When resubmitting it clears all the previous correct answers and jumbles up the order of the answers, just petty and time consuming to re-fill the questions you already got correct.

Having no background in linear Algebra made it difficult to complete the quizzes, assignments and exams. Even with the instruction (which was good) I found the hands on portions to be different from what was being explained in the videos. I will instead have to take the key concepts and do more research on my own to fully understand them.

Let me first thank you all for the effeors that you put to make this course avaialbe on Coursera. The teachers are passionate and they have their unique ways of sharing their knowledge. However, I think some warp ups are needed after each cocept as at some point i got confused and did not know what we were doing this and that.

Like most of Coursera's courses there are no staff members available in the forums (which is extremely shameful for Coursera - repeating the same boring pattern over the years). Don't even try it if you have never seen linear algebra or python before. Otherwise, it's useful for practicing a few concepts or refreshing others.

Nice course, with many insights. Sometimes the topics are given too quickly, I would have rather preferred less arguments but discussed more thoroughly. Nevertheless, I think this is a good one, especially if you've already got some background and you're looking for some general content to build upon it using academic books.

Overall, I learned some new stuff in this course. The programming exercises were interesting. However, the instructors really should provide more explanations regarding the calculations, formulas, and exercises' instructions and feedbacks. In many occasions, I had to looked up explanations online to solve the homework.

The videos are super nice and professors are excellent at explaining the concepts. However there's a big difficulty gap between the lectures and the assignments and little to no feedback when you have difficulties solving the problems. Plus, the programming assignments are just not covered in the lectures.

Very challenging and interesting. However, the last module was a bit confussing and needed to look for materials on the Internet to really grasp a bit of understanding on the subject. Although sometimes frustrating, I think it is a good start to recap mathematics with a very practical approach.

Overall, it was a good summary to understand linear algebra. To get into the topic, I had to read through additional material as the videos and tasks provided in this course were a little shallow to my liking. I, personally would have liked more applicable machine learning examples.

I believe that the programming required in the assignments are not beginner level. I had never coded on Python before and I thought that there wasn't enough support on how to test my code before submitting, for example. On the other hand, the math topics were really interesting.

I give this a three because the course focuses on themes with a macro lens while not giving the microdetails much explanation. Good foundation and interesting topic, but it seems counterintuitive for me to have to supplement the lectures with youtube lectures...

I felt that the course does not provide any concrete examples of solving for scalar and vector projections and we're left with searching online for those which makes the course at least in the areas of scalar and vector projection confusing.

Decent enough. The quiz are hard because too many concepts are not covered. For example, row reduction, gaussian elimination and that one quiz on Einstein summation. Good introduction, but not for absolute beginners. Good lecturers though.

It was too fast for me. I answered many questions just by chance. But i got an overview of the concepts like diagonalisation , inverse, transpose, basis, span , eigen and so on. I am hoping that i will build on this.

I searched a lot of additional information in order to understand something. This is the most disadvantage of this course. Nevertheless, the course have many exercise and labs, which were interesting.

The course objectives, aims, and motives were very clear but after mid week 3, the teaching became abstract and the professors should have given little more explanation about the advanced topics.

I am feeling like something is missing during the last part of the course when it comes to Page Rank Algorithm. There should be more explanation to how the math works or comes to its formula.

The assignments kill this course, great instructors, and pace, in my opinion. (I am a beginner in linear algebra and I understood the concepts without needing Google or external resources)

I think the course is more suitable for those who have had comprehensive theoretical knowledge in linear algebra and intend to learn more about its practical use and its relevance to code.

The course is good. But the last module (week) is not so good. I think that the explanation of the Page Rank algorithm is not very good. I also think that the final test is very confuse.