The course should be longer and build a stronger foundation in order for the assignments to not feel disconnected from the instruction. There was a large amount of redundancy from previous courses. The PCA instruction from week 4 needs more development/insight. Great specialization overall. Part 3 needs more work though.

This specialization course was really challenging. While I do understand that PCA topic is tough to cover in just a month, the concepts can still be explained down to our level like it wass in Calculus and Linear Algebra specialization. However I liked the course and thanks coursera for this wonderful journey.

Thank you to all the professors and staffs for such a wonderful program. I did learn a lot.

This last course is indeed a fun and challenging one. But it fells short compared to the other two due to some aspects which can be improved in the future.

Nevertheless, I'm glad that I can learn about PCA.

The course contents were good, but I felt the explanation was not so clear. Since PCA is a very important topic in Machine Learning, after explaining some new concept, the instructor could've solved a couple of examples with it, so that the newly registered concepts would be crystal clear.

Course content is very awesome. The instructor also teaches in a very splendid manner which makes it very easily understandable. But the evaluation method for practice exercise is very worse. Code get stuck for hours. It's been very frustrating waiting for code to get compiled.

This course is way more brutal than the two previous courses in the specializationIt is also very mathematically oriented, it lacks the graphics / animation / intuition that was given in the first two courses.However, if you make it, you indeed have a good understanding of PCA.

A lot of input in relatively short time, main points could be pointed out better in the videos. Assignments were tough but manageable, the instructions could be clearer and more detailed. However, being pushed to figure out things by yourself is also a learning opportunity.

To me, the first 3 weeks in this course is good. But the 4th week is quite confusing. And I don't understand the applicable meaning for the materials in the 4th week. I may need to review what I learned in the 4th week and then decide whether I understand it completely.

Good stuff:

Instructor has good knowledge of the subject. The course content structure is designed well.

Bad stuff:

Concepts could have been presented with more clarity. Programming assignments need more instructions and less assumption on what the students already know.

Quality of the course is great, but I would question whether it belongs in this specialization given the huge jump in expected knowledge from the first two courses to this one. Relied alot on the forums and YouTube to gain sufficient knowledge to complete this course.

the course handles important topics but unfortunately NOT well covered in the videos, the instructor assumes previous knowledge of the topic I guess! The MultiVariable Calc course was amazing from start to end I expected at least the same quality :(

Instructor has done lot of hard work. However, the course is little rigorous. If it is possible, I request the team to upload few more videos for this module. Nevertheless, thank you so much. I have still learned a lot from this course.

The content is decent but there are some bugs in the programming assignments. Particularly the last two programming assignments. The auto-grader for the second to the last assignment passes in some input that is not of the correct form.

The course content was very good,but the assignments were harder as knowledge of python libraries was required. It would be very helpful if you change the assignments as I feel the course should rather be about math than python

The first three weeks courses are ok and can follow, lecture in last week are very difficult to understand as the teacher skipped some of the steps and straightaway gave the derivation and lots of bugs in assignments.

Positive points: At the end of the module, you get a good understanding on how PCA works. It fulfill its objective.

Negative points: The assignements are poorly directed, the material is not always clearly explained.

Good Course, but

Too less examples to do the quizes on the first run.

Programming assignments are not clearly stated, so you need unnecessary much time to succeed.

I liked the Linear Algebra & Multivariate Modul more!

The course is Satisfactory.The content is Good,no doubt about it,but many topics(both mathematical and computational) were unknown and coding assignments of Jupyter notebooks of this course(PCA) are very Buggy

Kinda complicated but doable. The stuff do not monitor the discussion forums unfortunately. Without Susan's detailed & well informative replies I won't be able to complete the course. Big THANK YOU to Susan.

The course is interesting, but some of the quizzes were not done very well. After the first 2 parts of this course, which were just amazing, this one seems kind of worse, although by itself its not that bad.

They need to slow down while explaining concepts. The instructor assumes the viewers know each and every step. The other two Mathematics for Machine Learning courses were much better compared to this.

I was expecting this course to connect with the previous two but it turned out to be self contained. Jupyter notebooks contain inconsistent comments and assignment steps. Certain tasks were not clear.

The jump in difficulty for the final two modules was too hard going from the previous two courses in my opinion. also I would have liked more practical examples rather than being directed to reading.

Difficult course. They need more formal tutorials to help with the gap between the videos and the tests and projects. I found it very helpful to buy the instructor's textbook and read along in it.

Amazing topic, great teachers and nice videos, but assignments can be slightly frustrating and some aspects (matrix calculus, derivatives, etc.) are really expedited... Still worth your time!!!