Learned the math behind Deep learning, which is essential for understanding why the algorithms work, the last assignment could have been improved a little bit, it seems kind of a rush while working on it, keeping track of all the concepts.

I like this course because of the high quality in teaching linear algebra and Numpy to solve some problem . Also I learned Matrix as well as and I'm glad to participating in Linear Algebra for Machine Learning and Data Science course .

Very good course. Very well explained. In some places where we are connecting to previous video if you give the video as connection to the current video it will be very helpful for those who have a considerable time gap between videos

There are some errors on prompts and notebooks that made it difficult to understand some topics (until I get that the error was not being made by me). But in general, it was an excellent experience for me.

I am grateful for this course. However, IMHO, eigenvalues and eigenvectors could be explained in a more clear way. I would consider revising the last two pieces of video and recording them again.

it's was a great experience and the explanation was easy to understand. I want to thank everyone who works on this course. but I have an suggestion that labs supported with visual content like videos

Some stuff left unclear & issues in some notebooks, otherwise great, I appreciated all the graphs explanations that made the course more understandable than when I had learned it at school

A bit more detail into the complex topics of eigen values and eigen vectors would have been helpful. Also notebooks could have been oriented more towards the practical use of the concepts.

the first two weeks were clear and easy to understand, but then the last two weeks it gets more ambiguous and harder to understand even if i repeat it. overall it was an amazing course

I enjoyed the course very much but I found that week 4, especially the Eigenvalues and Eigenvectors explanation were not complete. This section can be definitely improved.

Well explained and well paced. I had more trouble at the end with the Eigenvectors series. Since I had no prior programming, I did not do well with the Python labs.

Great course with easy to understand material but it doesn't have any videos in programming lab section and is confusing in some parts in the beforementioned labs.

I face some difficulty at the python part, since I have a tiny knoladeg at that part other than this every thing was really good! I enjoyed the course.

Opened my eyes about the concepts i've learned in my UG studies...which i've been wondering how to implement practically, especially in ML and DS : )

It's a great course with professional professors but there is one problem i hoped they made lab lessons videos but overall I loved it.

Good course, programming assignments were partially too easy. Portion around eigenvalues and eigenvectors appears to be a bit rushed.

The course was excellent – clear videos with great content, and the problems were set at a good level, as were the programming labs.

This course is awesome because of the explanation and examples of concepts .It could be better if some things are shown proof

The instructor was well versed with the concepts although if some coding could've been taught, it would've been even better.

The eigenvalues and eigenvectors week is not clear and seems to have been rushed over. Otherwise the other weeks were clear.

He was confusing at time but the basic revision of all these concepts and how it links to machine learning was helpful .

the lesson is insightful but also a little bit difficult. maybe I need more time to rewatch the video to understand

I'm overwhelmed at coding sections, I'm soo confused that i started crying, but overall, that was great experience.

sometimes it's hard to understand, but it's really cool! Thank you to everyone who helped to create this course!

It's hard but I loved it. I would have preferred the instructor did more labs or a video of them doing the labs.