nice

good

good

gud

Nil

thx

-

No

..

ok

Ok

ok

5

.

This class was well done overall. The videos were mostly the right length, very well done and real reasons for learning things were made available.

The only reason I didn't give it 5 stars is because I found several times that information seemed to be lacking, especially in the solutions to the problems. At a high level often the process being taught wasn't what was used in the solutions and it was common to be a trick which was fun to see, but when struggling to understand the concept a fully step by step example would have been much better. I missed a problem on one of the quizzes because I didn't understand how something came together, but I did figure it out later, but it was because the exercise was just to simplified and not worked out for me to see the method.

I also found that at least for me the time spent was much longer than estimated. Sure I haven't done much real math in a long time, but I didn't expect things to be quite so difficult to keep up with on time as it was and it stemmed from not having clear examples with enough details and left to do research on my own to fill in some gaps. Occasionally in a future video after a problem set, something was made clear, but by then I often researched and found the info on my own, leading to perhaps a slightly out of order or lack of organization around the videos.

A very solid introduction to basic linear algebra (LI). The course provides a useful and concise roadmap for someone who is independently learning LI online, like myself. The professor provided a solid overview of each of the major topics through his videos. I was able to use this course as a roadmap to doing deep dive into each of the specific concepts.

The downside of this class is that it is highly compressed and only offered a "tourist" view of LI. The course didn't dive into a detailed explanation of the real-world meaning of key concepts such as Null space, Column Space, amongst others. I needed to independently search out additional content and videos to better understand these concepts on why they are important and their respective applications.

Overall, it is a very good starter class for LI but it is not sufficient for someone who really needs to learn LI for further applications such as aritical intelligence.

The course is OK, but can be greatly improved. First, as usual for Coursera, it is very short and squeezed. I wish this would be a regular semester-long class that would cover topics in more detail. There were some places where I found lectures not quite clear. Some lectures (e.g. eigenvalues of diagonal matrices) were outright missing. I often had to go to the Linear Algebra texbook by M. Cohen - just to understand things. Although that's what is probably expected from any course. Too much emphasis on solving problems that involve lots of arithmetic using pen and paper. Very time consuming, considering all the arithmetic you need to do.

Some part.,e.g., row and column sub-spaces, orthogonal projections, were very abstract. Intended for the purist ?

Found it tricky to determine linearly independent relations in matrix form.

Seemed like a bit of big step change between the lecture examples and some of the problems.

The practice exercises and quizzes were a good idea; again one or two seemed very theoretical. But they do help in the understanding of the material via more concrete examples, in the main.

Thank you it was an overall enjoyable experience even though a bit taxing in parts.

Great course. Great instructor. Just a bit of lost feeling for some concepts/formulas whose use is said some videos later. For a few moments I felt like not knowing where we were going to, and for me that's important. Other than that, i strongly recommend this corse. It has all the important concepts for applying linear algebra and matrices on engineering and other science fields, and the instructor explains them in a very understandable way.

A good refresher course on matrices. learnt a lot. the course would be much more beneficial, if number of examples and problems are increased. also the professor needs to demonstration the matrix operations graphically, as it becomes sometimes hard to grasp the abstract concepts. week 3 is the hardest and need further explanation as well. i had to struggle with the quiz of week 3 a lot.

Overall a good course. Want the following improvements:

1. Cover topics in vectors (dot product, cross product, scalar triple products)

2. Use MATLAB to and show more realistic examples that can be applied to real life engineering and science applications. After all, this class is called: "Matrix Algebra for Engineers".

Thank you professor Jeff for your teaching.

Sincerely,

Shulin

I enjoying this course, a lot of explanation can we get here, but sometimes there's an explanation that i don't really understand, so i searched more in google, buat overall this course is good, and i like the exercises and the way its showing the explanation in the answer section on the e-book, and the e-book is good too.

I strongly recommend this course to students who want to study Machine Learning. I did this course in parallel to the Stanford University Machine Learning on Coursera. This algebra course is crucial for students to understand how gradient descent, principal component analysis, and linear regression work.

Covers the problem solving aspects of linear algebra. If your aim is to get better at solving linear algebra numerical, this course is very useful. If however, you are looking for an intuitive understanding, try the course offered by Imperial College instead.