good

good

Nil

thx

-​

No

..

ok

Ok

ok

.

5

.

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.

I loved the content and the tests, although some of the concepts could benefit from a slightly deeper explanation. For example, going from a 2X2 matrix in an example to a 4X4 matrix on the test can be daunting.

This course is an easily achievable course, it has several challenging topics which are taught thoroughly without any complications. These videos are made audience friendly and it's a generous offer in Coursera.

I am finding this course very useful as a refresher. This course does cover most of the concepts needed and used in engineering. I sincerely thank the professor and his team for making this course happen.

Sir ypu make it understand well. Your teaching way is good. I appreciate you for this sir... Thanks for making these videos as it will be helpful for us in future also.....

A very nice course, however in some topics if there were more examples it would have been more clear, Furthermore, it was very hard to finish the course in 4 weeks.