I really enjoyed the course. Great learning experience. There's one area where I felt that the course could have done better. And that is explaining the interpretations of various mathematical calculations. These interpretations were embedded in the quizzes and the assignments. But they were very cryptic.

The videos and materials are great, departing from zero in the subject I was capable of understanding and practicing., but some programing exercises demand any knowledge in python, what makes things more difficult in a few moments. Would recommend for anyone that wants to enter into the ML world.

It is a good course but it is annoying when the quizzes jump into concepts that werent described in the videos, though I understand they are trying to make it intuitive, it can be very frustrating. I definitely have a much larger understanding of linear algebra and Python than when I started.

Filled in a lot of knowledge gaps that I should have learned in high school or undergrad. I feel much more prepared for graduate studies in data science.

4 stars because the last module felt rushed. I felt that I learned more from trial and error on the quiz than from the lecture videos.

The content is good, and I can see that the instructors are trying to let students understand the mechanism behind the calculations. However, the lectures are too short for students to fully understand everything. I would suggest to extend the length of the videos and provide more details.

Very good class. Outstanding instructors very clearly teaching key concepts in linear algebra.

I only docked one star for two reasons:

I wish they explained in more depth how the linear algebra topics are used in machine learning.

I wish the class were a little longer and more in-depth.

Mathematics is the core of machine learning. This course is best for understanding the mathematics of machine learning. The course was in-depth and intuitive. The assignments were a bit difficult for the new programmers. But overall, the theory classes were clear and understandable.

While they explain the basic concepts of linear algebra, sometimes the programming assignments are tricky and some of the quizzes are too complicated to complete with our current knowledge. However, the course is worth taking if you want a solid math background for machine learning.

the lectures were very good and on point, obviously referring the prescribed textbooks will further improve one's knowledge about the subject. i really enjoyed the programming part of the assignments, which were made to help students without any prior experience of python language.

It would be better if it pointed out the pre-requisites of this course. Besides, the submission process of Jupyter notebook doesn't work directly. These issues need to be solved. Other than these issues, the course itself is pretty informative and the instructors are well prepared.

Great course, offers a nice introductory base you can use to further your knowledge without having to take a full three month course on linear algebra, allows you to dig into some interesting stuff earlier on. Could have used a bit more feedback for quizzes and assignments though.

there is still some material that is still difficult to understand, such as material on Getting a handle on vectors, material on Types of matrix transformation, material on Solving the apples and bananas problem: Gaussian elimination, and material on Eigenvalues and Eigenvectors

The lectures are easy to understand. However, the quiz is slightly harder than the course material. Especially the first quiz (it gets easier in the end). The coding part requires previous knowledge of python. Otherwise, you will be so lost in the process. Overall, great course.

The instructors were great. They explained the topics nicely. But this course should add more clarification of different topics in the video section. And it would be great if the instructors could add some programming examples in the videos. Then the course will be more helpful.

The examples were relevant, and I could follow along with them on my own. The programming assignments helped to complete the understanding of the processes. I would've liked more examples to work through for practice, and to improve understanding. Otherwise, it was great.

Nice and simple to learn. You'll get intuition of what matrices do and ways to look at a matrix. However, like the instructors say, this does not include all of linear algebra.

I do believe it provides a very good gateway to reading further topics on linear algebra though.

The basic geometry explained by the tutor is amazing especially the dot product, determinant, etc. Although the program assignments suffices for its purpose, I would have enjoyed more if it would have been little more challenging. Overall, this course rocks on its purpose.

The last module seemed a bit hurried. More videos could have been made regarding the topics in the last module. The video on PageRank algorithm should have more illustrative examples for allowing the students to visualize. Apart from that, this was an amazing course!

Great course and expert instructors. Some assignments are insanely tough, did not understand the relevance of those questions to what we were taught in the lecturers. The content however is good to introduce you to the concepts and if you need a refresher course.

This is good course, anyway I miss a couple of things:

First, it is needed some experience in Maths, the concepts are explained by word in the videos, making some drawings. I missed some slideshows.

Secondly, it is okay if your familiar to Python's library Numpy.

The first three weeks' courses are a little too primary for me, while the last two weeks' courses bring some good insights with interesting examples. In a nutshell, this course is qualified as an introduction to the core of linear algebra and deserves a thumb-up!

This course is good for developing some intuition regarding vectors, matrix, eigenvectors. It would be very helpful if the final week had some more video lectures explaining things a bit more. The quiz is too tough if someone only base his study on the lectures.

some quiz were very easy to topic but some are were really hard i think there is a a little bit unbalanced questions in the course but they are effective too and i wish that i could watch or read solutions for this question because some are still complex for me

Excellent course and very practical; it's really focused on machine learning and there's the opportunity to learn some coding in Python. I would recommend it to everyone interested in machine learning. I give it 4 stars because there's always room to improve.

As I person who have 2 Masters Degrees in Law and Agriculture this course sometimes was to challenging. May be it's good reminder for those who have some strong math background, but you'll need to read and watch all lot of additional material in another case.