16 janv. 2022
With regards to my course and program, this was relevant. Although I was behind on some weeks, it was because some of the topics were not in concurrence with my course, but this course really helped.
4 août 2021
This is a carefully sequenced, content-rich introduction to Matrices; beware skimming over details: eg. the use of matrix formalism to solve the least squares problem is little short of magic.
par Parinda b•
27 mai 2020
par George G•
23 janv. 2021
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.
par antonio q•
3 mars 2021
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.
par khawar n•
1 avr. 2020
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.
par SHULIN J•
16 août 2021
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.
par Nur I H•
2 janv. 2021
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.
par David F•
19 janv. 2021
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.
par Arjun V•
27 juil. 2020
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.
par Dhiraj S•
28 janv. 2021
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.
par Vishnu N•
5 nov. 2019
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.
18 sept. 2019
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.
par Naman S•
21 juin 2020
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.....
par Ibraheem B•
13 févr. 2021
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.
par Abhay G•
11 août 2019
This course is not only very helpful for engineers but also helpful for under Graduate students.
I like "Gram-schmidt orthogonalization process" based lecture.
par Rajashekhar P L•
6 juil. 2020
Good course, it was really informative, if some numerical methods were to be included it would enhance quality of course.
Thank you Professor Jeff Chasnov
par Akash D•
11 janv. 2019
Very systematic course ,not a typical first course in linear algebra but brilliant overall .Extremely useful for engineers.
22 mai 2020
overall good experience to learn this matrix,but few engineering examples but a strong foundation for linear algebra concepts.thank you, sir.
par Kishan S•
23 juin 2020
It helped me to understand the various methods of matrices and solving methods...And the applications of matrices in engineering carrier...
par Aiyetikun P B•
21 sept. 2020
It was an interesting course, and it was excellently and structurally organized for well and proper learning, I really did love it
par Cody L•
17 avr. 2020
I thought it would be helpful if we were given more practice problems to do on our own so that we understand the material better.
par Luiz C•
24 mars 2019
Good, but would have appreciated slides instead of just pdf, and tests are too much on manual calculus instead of thinking...
par Arie S•
6 août 2020
the more abstract side of algebra is important. without that side it is hard to know when to use the stuff you taught us
par Євген Ш•
2 mai 2020
Course is very well explained, but it feels like one introductory lecture into the topic rather than the whole course.
par Joseph P•
8 août 2019
First 2 weeks was clear as day, 2nd 2 weeks less so at times (for me). Thanks very much to Jeff & Coursera.
par Gustavo M C•
14 avr. 2021
Very straightforward however still need clarifications with regard to solutions for problems/questions.