Good details, great at building intuitions. Instructors are pleasant to listen to :)

As expected, it's enough to get you going in the right direction, that if you want to know more, you'd have enough knowledge to build on from.

Lack of support from the staff. Some parts/lectures are not clearly explained (for example, constrained optimization) and some quiz questions are not directly related to the course content. Otherwise, it's a very good course.

up to week 5 , it was masterpiece.

week6 (although it should be the most important one) was a mess and disappointing.. as it was not explainable, i couldn't link what is happening with previous weeks.. require to be enhanced

This was a good course. The instructors kept me interested in a rather dry subject. The exercises were well designed. There are courses on Coursera which are not worth the time. This course is not one of those.

The first 3 weeks is really good, the fourth week is okay but the last 2 weeks is kinda confusing. The explanation is quite clear but it is quite hard to grasp the intuition and relationship between each material.

Along with the advanced and popular technique, this course gives me impressive insight over how machine learning works. But it would be much better if the concept in linear algebra combines more with this course.

I thoroughly enjoyed this course. The materials were good and the course content was good enough to pass all the assignments and quizzes. This is way better than the linear algebra course in this specialization.

All was great until weeks 5 and 6. For these weeks, there weren't enough explanations in order to really understand the subject. Some very important steps were simplified, which made understanding difficult.

i think some of concepts touched the surface and it was difficult to get a deep understanding .Probably the course could have provided some external links for those topics where people could read .

Superb quality. The way instructors teach is really innovative. The course is good in terms of the area it covers but lacks depth, but is a good starting point if you want to dwell more in detail.

Very informative refresher on the basics of differentiation, though some of the later topics could have been fleshed out more (i.e. Taylor Series, Lagrange Multipliers, etc). Overall very good.

This course is good in general. But some parts, like the Lagrange Multipliers, needed better explanation and more exercise before testing. I also missed more supplementary material.

I wish, Linear Regression was taught with a little more clarity. Seemed like too many things were happening. Otherwise, a very good course. Really enjoyed the back-propagation week.

the basic concepts are explained clearly, but the step of the lecture became more fast than the course of linear algebra. More detail proof and application of theory is expected.

The course starts off somewhat too basic for my taste but still gives a great intuition for some off the fundamental concepts underlying gradient descent and machine learning.

The course is still a bit young, some errors appear here and there sometimes, and some parts of it are a bit steep.

Otherwise, this is a good course, focused on derivatives.

They should explain concepts in detail. They just explained really tough concepts in 5 min and gave much much harder assignments which was really frustrating at many times.

The assignments are too cumbersome for just testing concepts. This course is definitely for experienced students. i found myself being confused by concepts i already know

This course opened my mind to a whole new view of calculus in general, thanks guys for that incredible work. with that said, the course needs some tweaks here and there!

Practice makes about 65% of this course, 3Blue!Brown and Khan Academy are indispensable in this course too. The course is more like an overview than an in-depth study.

Definitely not for beginner, but for someone who already had knowledge about multivariate calculus, it is a succint course for you to review and gain some intuition.

I don't know if it's because less important or something. But the explanation of Professor David in this course is confusing especially in Lagrange Multipliers.

1.Week 5 should be taken in separate module dedicated to statistics.

2.The duration of course can be increased.

3. Week 3 and week 4 can be made more detailed

Very good course but especially while approaching the end of the course some steps are being skipped or not explained entirely which can be a bit confusing

This course is a good refresher, bringing all the important aspects and how it can be applied for machine learning also combining with linear algebra