This is a great course. It covers the topic in good amount of detail. I have enjoyed this course a lot and it also made me think deeper at a lot of places. I am motivated to go and do more work on related topics now.

The course was great till the final week. The lectures did not explain very well the concepts and the assignment was poorly designed. It's a shame because I've loved the more rigorous way of this final course.

I think it's really a hard lesson for me, but I've also learn a lot, thanks a lot for the teacher and coursera. Some Programming test take too long to execute, and there are some errors in it. just be careful

Finally understood basic intuition of PCA, never got perfect resource before. However, there was a sharp change in terms of course delivery than the previous two courses of this specialization. So, heads up.

Great capstone for the three-class Mathematics for Machine Learning series. Assignments were way harder and programming debugging skills had to be appropiate in order to finish the class.

Course content tackles a difficult topic well. Only flaw is that programming assignments are poorly designed in some places and are quite difficult to pick up at times.

Teaching pacing is good, and clear in explanation. It will be good if there are some examples about how we should apply all these theories to some real problems.

I learned a lot in this course, though the last week was somehow hurried and the lecturer didn't spend enough time to piece the whole stuff together.

A different course than the previous 2.

Much harder - as you have to actually know some Python tricks.

But I guess it's the same in a real world.

Course addresses important subject, but I worth like to have more in-depth explanation of the mathematics by the instructors and more examples.

Felt like explanations in this course were a bit confusing, but otherwise, it was a very interesting course. Thank you so much for doing this.

This was a very hard course for me. But I think the instructor has done the best possible he can with presenting and explaining the course

Coding assignment is hard for people who are not familiar with numpy. Would appreciate some material at least going over the basis.

The course level is very difficult and I think having four week course is not enough to understand the math behind PCA

That's a great online courses can help people have enough background to break into Machine Learning or Data science

The PCA derivation part requires more elaborate explanation so that we can understand the concept more intuitively.

Overall the hardest of the specialization, a though one but great to make sense of all the maths learned so far.

Programming assignments are a little difficult. Background knowledge of Python is recommended for this course.

Very difficult course, make sure to do the prereq courses first and understand everything from those courses.

The derivations of some concepts have been more vague compared to other courses in this specialization.

-Some of the contents are not clear.

+It gets great intuition for new learners in machine learning.

Lot of Math. Couldn't get proper intuition regarding PCA, was lost in understanding math equations

I agree with the others. Course didn't merge well with the 1st two which were perfect!

still have room for improvement since lots of stuffs can be discussed more in detail.

Harder than expected, the content is good and is well worth the struggle!