The style of teaching is great.

found the course too basic

Good Teaching

challenging

good

NA

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.

sometimes David just keeps talking about some underlying relationships between the concepts, or doing a bunch of operations, while he writes nothing down or just not provide any visual representation. when he does that its very hard to follow, and i have to replay the same video 10x trying to visualize what he is talking about in my head.

the biggest issue is that throughout this whole course (atleast by week 4 that im on so far), is David did not go through any real world problem examples except for a very simplistic example about store prices, which happens to be the same example that is used by every other teacher. seeing more examples would've definitely added more value.. since many of us are learning this in prep for real applications like data science.

the university should've also put in more effort to create computer generated animations and visual representations of everything that is being taught. Linear algebra is the one of the subjects that requires the most visual intuition, so whoever decided to skip the effort on this should be fired.

that being said, i do appreciate that David tries to explain the concepts in depth and connect the dots between them. this has still been a valuable learning experience to me

Course: Definitely target for people that have solid understand of linear Algebra

Professor:

Pluses: Nice and clear voice, nice demeanor, good energy

Minuses: Long and sometimes messy samples presented on the board, not following through with the samples given (changing subjects causing confusion)

Area of improvement: It would make more interesting if would make connection with real life situation where we could make use of the classes. The instruction video made the class appealing because started with an example of a real life situation that could be resolved. It would be wonderful if full course would bring same excitement.

Exercises/Tests:

Pluses: Unfortunately there was no plus on the exercises. I hate to say that was all pretty bad.

Minus: They were confusing. A lot of time did not make connection with what was taught.

Area of improvement : Give explanation of the answers on the test itself and not referring back to the class. Resolving one to one exercise help making sense of the course being studied.

Course overall was not good. I am very glad I did not pay for this class. However I do think if the professor changes a few things he can nail this class same way he nailed the intro.

I am new to Coursera so I have no idea of what is standard on here. Maybe this course is good relative to other courses on here, I don't know. However I do know that based on my experience I can not recommend paying for a coursera membership to take this course. This course comes with a total of less than 3.5hrs of instructional video. Considering linear algebra is usually taught with ~45 hrs of classroom instruction, this may seem short.. and it is. The course does a good job at explaining things at a conceptual level however it has few worked through example problems. The course uses quizzes and programming assignments as a way of reinforcing skills that you learn however the correct answers to the questions on quizzes are never reviewed. So if you get something wrong you'll never know what you did wrong unless you figure it out for yourself. Also the forums don't seem to be useful at all. If you are lucky another student might reply.

The time commitment is not realistic unless you are a math wiz and experienced programmer. Take the timelines and multiply it by at least 5. Videos do an excellent job of presenting theory and application, but there is no supplemental learning material. You can have to find all of that on your own. In general the other students in the course are lost and have no idea what is going on. I recommend that you watch the videos and follow up the subject on something like Khan Academy where you can work through multiple examples. As for the coding part you need to find someone that knows how to code math in python. Would not recommend.

I don't think this is a good course. The explanatory videos are not bad and they are easily understood, but they seem to be a series of unrelated concepts, you wouldn't know why those concepts are explained and where the lecturers want to go. There were tasks that had a much higher level of complexity than the videos and other tasks that were trivial. As if that weren't enough, I had repeated problems due to text format in the questions, since it was difficult to distinguish the vectors and matrices.

Very challenging to follow instruction at times. Needs to update videos so a bit longer in order to effectively teach the content. Errors with calculations in week 3 with the Composition or combination of matrix transformations video. I've also had to utilize external resources to adequately understand what is being taught. I've taken other courses through Coursera and not had this level of frustration with the other courses.

Not a fan of this course unfortunately. They jump straight into examples before going through the formula and whatnot prior. For the most part this is fine as it is all fairly straight forward, but a few times the lectures where hard to follow.

Most annoyingly were the programming assignments. Not explained at all in lectures, and for someone with Jo programming experience it was really frustrating to get my head around

This course isn't for someone who is going with no knowledge of algebra, the examples are superficial and on the quiz they ask for what they didn't teach. I recommend to learn algebra before hand, I took more time to learn in other platforms what they were trying to teach over here learning with them. So go buy an algebra course and then come back here, you will be able to take more advantage of this course.

Useful insomuch as it highlights the aspects of linear algebra that are key for machine learning. The lectures and exercises help you get the basics, but if you have any questions, don't expect any help from the forum. I would strongly recommend following MIT 18.06 alongside this course to gain a more solid foundation and because the lectures in 18.06 are genuinely enjoyable.

Too many important elements are skipped in the videos. Either the videos should present the material needed for the quizzes or they should pause and link out to other resources that explain things in useful detail.

The instructors' enthusiasm, while very inspiring, does not compenstate for the fact that material relevant to the quizzes is either glossed over or missing.

Videos are good and some activities are very intuitive.

But every now and then a quiz is thrown in without instructional videos support it, this makes you feel lost and hopeless and there is no teacher support in the discussions to help.

I had been enjoying this course but the lack of basic support really leaves you feeling lost and stupid.

Great instructions. Instructors appear knowledgeable and eager to convey the subject.

Programming exercises are however of very poor quality. Even correct answers are not accepted by the automatic grading system due to its brittle design. Fledgling python programmers run the risk of picking up bad coding habits due to poor code style.

I think that the course is fast-paced and skips building conceptual knowledge. It is understandable that the online course may not be as interactive as classroom programs, in which case, instructors should give some reference to reading material or exercise books to come up to pace with the speed they are flying with in this course

please don't keep the programming quiz ,its irrelevant for what we are learning, because many may not have programming knowledge but they may be strong in maths this will restrict them from appearing .

but overall the video classed are awesome.thank you so much for giving us this opportunity.once again thanks a lot.

Not enough explanation. You learn how to do problems but you dont really understand it on a deeper level. I was able to pass the course but I dont think I learned much passed the examples given. Also, I think for the practice quizzes it would be beneficial to show how to get the correct answers.

Quizes and practice material were either overly repetitive or were not supported by the materials. If the course is based on exercises, then a bit of time should be spent on review of the solutions and methodologies for solving. The forum is fairly disorganized so did not solve this purpose.

I did not enjoy this course. The videos were good but covered the material very quickly and did not leave you well prepared for the assessments. I found the assessments impossible without a lot of extra study using other materials - if this is intentional it should be made clear.

1) There are not enough examples on some subjects 2) The instructors explained the theories and intuitive behind it very well, but the exercises are sometimes too difficult 3) Coding exercises are very challenging and I'm not sure what good it could bring to my data science journey