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Avis et commentaires pour d'étudiants pour Matrix Algebra for Engineers par Université des sciences et technologies de Hong Kong

2,051 évaluations
561 avis

À propos du cours

This course is all about matrices, and concisely covers the linear algebra that an engineer should know. The mathematics in this course is presented at the level of an advanced high school student, but typically students should take this course after completing a university-level single variable calculus course. There are no derivatives or integrals in this course, but students are expected to have attained a sufficient level of mathematical maturity. Nevertheless, anyone who wants to learn the basics of matrix algebra is welcome to join. The course contains 38 short lecture videos, with a few problems to solve after each lecture. And after each substantial topic, there is a short practice quiz. Solutions to the problems and practice quizzes can be found in instructor-provided lecture notes. There are a total of four weeks in the course, and at the end of each week there is an assessed quiz. Lecture notes can be downloaded from

Meilleurs avis

30 avr. 2020

Very in-depth class for matrix algebra. I am a biochemistry student and have learned this in the past but re-taking this online course again has revamped my learning for linear algebra.

6 nov. 2018

Very well-prepared and presented course on matrix/linear algebra operations, with emphasis on engineering considerations. Lecture notes with examples in PDF form are especially helpful.

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476 - 500 sur 557 Avis pour Matrix Algebra for Engineers

par shubham j

15 mai 2020


par Kakadiya P R

14 mai 2020


par nakka g

9 mai 2020


par Pulluri R

3 mai 2020


par Adavikolanu M C S S

29 avr. 2020


par Ravi B

27 avr. 2020


par Dr. T A K

23 avr. 2020


par Badhavath A K

22 avr. 2020


par Narasimha r c

20 avr. 2020


par Kaushal J

2 nov. 2018


par Vaishnavi

28 sept. 2020


par محمد ا

23 avr. 2020


par P P K

24 nov. 2020


par Jayantha N

22 juin 2020



4 juin 2020


par Thatikonda R

30 mai 2020


par Pavaneshwar r

22 avr. 2020


par Parinda b

27 mai 2020


par Rajeev N

3 juil. 2019

This is a really good class to get started on to the world of Matrix Algebra. A little knowledge of vectors would help greatly but not necessary. Writing notes while Jeff explains , helps a great deal with quizzes.

Jeff explains the material well in a very patient way. The quizzes are challenging and at the same time not too easy or difficult. Quizzes are very well designed to reinforce the material being explained by Jeff before.

PS: Great Class.

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 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 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.

par Surendar

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 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.