Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.
Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.
By Carlos R T G R•
The videos need to be updated, there are quite some errors that are already identified...
By Roberto V•
Lack of feedback or more help from instructors to doubts, but the course is very good.
By rishabh t•
Explainations was good but some topics was difficult to get may be due to my basics
By Adam R•
Some of the quizzes go beyond what is in the videos and often spent ages on them.
By Nicholas K•
Enough gaps that I finished feeling like I really had no idea what was going on.
By David R M•
Requires an understanding of python that doesn't seem to be expressed anywhere
By Jose H C•
I did not see any specific application of what was learned to Machine Learning
By Tory M•
All in all this course served as a good refresher for linear algebra.
By Gary M F T•
Esta en el idioma inglés. Seria factibles en el idioma español
By Alejandro T R•
Really difficult to understand the explanations of the course.
By Ayala A•
The course is good but the explanations are not clear enough.
By Ninder J•
not well explained...Rather than this go for khan's academy
By rajiv k K•
Good for rivision but I will not recommend to beginner.
By omri s•
Good, but a lot of stuff is not explained in detail
By สิทธิพร แ•
some lessons don't cover knowledge for assignment
By Flávio H P d O•
explanation not very clear
not enought examples
By Rosana J B•
muy confuso el sistema de envío de tareas
By Hiralal P•
they should provide more examples
By Neha K•
The style of teaching is great.
By Lieu Z H•
found the course too basic
By Jadhav J N J•
By Rafael L A•
By Navya V•
By Amit V•
1.) This is definitely not a course for beginners, especially if one does not know how to code OR if he/ she is weak in coding.
2.) As far as lectures are concerned, the faculty members/ lecturers are energetic. While some topics have been explained really well, many topics are either left without much explanation. There are some occasional mistakes on the part of faculty, which must've been edited and rectified. They have done good job in converting the lectures in to text. However, there were some mistakes in those texts too.
3.) There is no support in discussion forums from the lecturers of this course. I have seen many questions remain unanswered for many months. This is a very big drawback.
4.) There is a huge gap between what is being taught in videos and what is being asked in assignments. We can understand this by the following corollary: In the video tutorial one teacher is showing that 1 + 2 = 3. In the assignment, students are being asked to find the roots of a quadratic equation.
5.) Some questions and even their answers too technical to be understood by many students. The attempt to explain after the completion of assignment is also too technical. There should be an attempt to dive deeper to help weaker students. If time is the constraint, then make another basic course and let that be a prerequisite of this course. But please, do not mention in the introduction of this course that there is no prerequisite.
By Fuad E•
It is a little messy: there are no clear definitions of Vector Space, Normed Vector Space, Euclidean Vector Space. Functions as COS and SIN are used to show basic concepts, orthogonal base, and so on. "Projection" concept always relies on base being orthogonal, projection being under 90 degree (what is 90 degree in vector space?), and space being Euclidean, although it is much simpler and applicable for just Vector Space (space without "norm" defined). Good introductory course for high-school; bad for University. Good for kids who just finished learning Pythagoras Theorem, SIN, COS, and basis of Euclidean geometry. Example of house (with number of rooms which is positive Integer number, and price which is positive Decimal) is not really a vector. Examples of non-Euclidean spaces and their applications in machine learning not provided (geometrical deep learning on graphs for example). Basic course for those completely unfamiliar with what "vector" is. Provided tests in Python are confusing because in the context we write vectors (and "base" vectors which matrix consists from) vertically, and in Python - horizontally. For example, [[1,2],[3,4]] is matrix, but it won't transform base vector [1,0] into [1,2]. This is confusing and should be mentioned before test begins.
Thank you for helping me to recall this knowledge. I finished three weeks; I may need to update review later.