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.

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!

This course is full of mathematical derivation, so it is kind of boring.

Overall a good course. Very limited introduction to Python though.

编程练习的质量不够高，不管是编程练习本身的代码逻辑、注释、练习的质量还是在答疑区课程组的答疑都不能尽如人意，对于编程练习并不很满意

Course was challenging , but learned the maths behind PCA,

Good content, just need to fix the assignments' platform.

Mathematically challenging, but satisfying in the end.

great material but explanation are a little bit messy

Good but slightly less deeper than the other two

The instructor is great. HW setup sucks though.

Too much non-video lectures (lot to read)

Good, short, overview of PCA

Many errors of homework

Needs more details

This course had a lot of potential but there were a number of inconsistencies, cut/paste comment bugs, that make it more challenging than it needs to be. The comments in the notebook exercises should be triple-checked with the text above to ensure consistency of variables. Far too often these would be mixed up, or the input/output descriptions would be incorrect. Or the unit test would have different dimensions. Lectures often left out steps - e.g. "because of orthonormal basis, we can simplify and remove a bunch of terms" - how exactly? A extra few seconds of explanations would allow students to follow more closely. Notation in lectures is sloppy - sometimes terms would be missing and then the video would quietly cut to a correction. "j's" and "i's" indices were interchanged frequently making the derivations how to follow. Also, this isn't a course on unit testing - some more tests should be included to help students debug individual functions rather than relying on the final algorithm (e.g. PCA to work). It should be explained why the "1/N" term for XX^T is not necessary even though it's in the lectures. On the plus side, the added written notes were welcome and fairly well done.