22. Dez. 2018
Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.
31. März 2018
Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.
von Sekhar G•
20. Aug. 2020
Being at an advance level of study, this course seems to easy to me but what I recommend is that any undergraduate or postgraduate student will definitely gain many interesting facts about linear algebra from this course.
von CARLOS M V R•
25. Juli 2020
It could be good to have more explanation about eigenvalues and eigenvectors because it is an important topic for data science. In general it is a very good course, you explained many topics in a simple and funny way.
von Arnab S•
21. Juni 2020
I enjoyed learning in this course. There are a lot of different aspects that are covered here which is very interesting but I course is not for absolute beginners. It will be better if someone has a bit of background.
27. Feb. 2019
Nicely structured courses with enthusiastic teachers. Interactive enough to keep you thinking (which is key).
Some errors here and there and short moments of not enough explanation. But all in all an enjoyable course.
von Naser A A•
11. Juli 2020
Great course to understand how linear algebra is related to machine learning. Focused on the concepts, and the concepts work rather than calculations. Would be easier if there was prior knowlodge of python and numpy.
12. Juli 2019
This is a great course. The only thing is sometimes the calculations are hard to follow. I wonder if it is possible to let viewers click through a calculation process at their own pace. But the instructors are great!
von Mrunal U•
20. Juli 2020
excellent course to understand the linear algebra as a tool for problem solving in machine learrning though it not help directly but give you the strong understanding the fundamentals which will help in the future
von Snigdha A•
13. Okt. 2020
Excellent course. I just wish the assignments were a little harder. The last assignment was the perfect toughness level. Made me connect concepts, look up stuff and actually get out of my comfort zone to learn.
von Rachana A•
23. Aug. 2020
I used to think that where are we going to use these matrices eigen values and vectors in real.. and I've got my answer from this course...Thanks to the professors who had given clear view on these topics...
von Александр Л•
1. Nov. 2019
Great instructors, excellent content. I would like to see more practical use cases of the material (at least as a self-study reading). And please add an explanation behind formulas for the eigenvectors part.
von Augustinas S•
3. Juli 2019
Fast paced linear Algebra, perfect to get refreshed. Might be too concise for those who learned Math not in English a few decades ago, will require to browse Forum for additional links to read on the side.
von Shaquille M•
4. Feb. 2019
Great primer. Covers most of the important themes of LinAlg needed for applying machine learning, and also provides really good intuition. Useful for those wanting to sharpen up before further study of ML.
von Debbie H•
2. Nov. 2020
Good content, animated and visually-appealing lectures - considering it is mathematics, assignment material and quizzes are helpful for review, but minimal support and feedback for questions or problems.
von Putuma P G•
7. Apr. 2020
It's a great course as a refresher, but for mostly folks with a lot of time. The assignments are fair, but sometimes it's dive-in kind of stuff, whereby the assignment itself is the instructive example.
von Valentinos P•
13. Juli 2019
An outstanding course which builds your mathematical intuition rather to prepare you for mathematical calculations. My opinion is that its contribution is significant in the pool of courses in coursera.
13. Apr. 2021
a bit rush course covering the most important part of linear algebra, give me a very good intuition other than mathematic notations! the course might be better to add some explaination on math side!
von Deval P•
10. Juli 2020
even though my code was right in the last assignment the grader kept getting timed out. it took 3 days to work and in the end the code was same. the course on the other hand was quite good and easy.
von Jorge V•
11. Nov. 2018
Great content and direction. Only negative is the sometimes frustrating experience with the Jupyter Notebooks: debugging what has gone wrong is very difficult, due to a lack of good error messages.
von Marco K•
30. März 2020
Be careful as a beginner in coding. It might be frustrating from time to time. I have spent the majority of my timing on the coding . At the end worthwhile, but did not feel that way at that time
von Milan S•
8. Mai 2018
Good, but sometimes it is neccessary to look for supporting materials. I took this course in combination with MIT course in LA and this offered another, more practice oriented, view on the topic.
von Tanmoy D•
7. Juni 2018
The course is a great resource to brush up on the fundamentals of linear algebra and learn about the meaning behind the math.It prepares people for any further courses which use linear algebra.
von Keshav B•
13. Juni 2020
This course was very insightful. The instruction was well done with expressing the intuition, but the process was left vague on a few concepts and required me to look up worked out examples.
von Lalpekhlua L•
17. Juli 2021
I think it is a great course. It is definitely not for beginners and I feel the lectures are somewhat rushed on some videos. It is best to view this course as a supplement and not as a main
von Sharon I•
27. März 2022
good videos and good instructors; programming assigments could be a little bit clearer in the instructions. Overall good for understanding the maths behind Machine Learning. Thank you!
von shashank s•
17. Feb. 2020
The course was good but it could have been better if the exercises had more difficult questions or probably a section with more difficult questions using the concepts that were taught.