This is a good course coming with a very good book which you can use to reference later on even if you don't fully understand what or how PCA derives.

The exercise & lectures were interesting and guiding you enough to pass all tests. Take note and reference the book are keys to succeed.

Very interesting and challenging subject: PSA, this MOOC together with the other 2 Mathematics for Machine Learning are one of the most useful I have ever made, actually they helped a lot in my other Machine learning and Deep learning studies! I highly recommend this fascinating MOOC

Perfect course. It takes up more time and effort than the other two courses in the specialization. But what you learn by the end of it is totally worth the effort. Note that this is an Intermediate course compared to the other two which are beginner. So the extra rigor is expected.

The introduction to PCA and steepest descent algorithms which might be a century old but still act the fundamentals of many state of art equations. So, you will learn the basics that how they function, and the real mathematics you need to know for ML using this course.

A really great course with mant well explained interesting concepts .. I personally liked the Python coding assignments in this course because it made me learn so much Python applied to very interesting problems .. Thanks for imperial college for such amazing work !!

Its a very informational and interesting course. I understood a lot about PCA in this amazing course.

It was a good addition to the previous two courses of the certification. I would like to get similar courses in statistics and probability useful in Machine learning.

Great course! It is a bit more challenging than the other courses in the specialization. It is great that this course is built based on two other previous courses. The lectures are great, the quizzes and programming assignments are complex enough to be interesting.

An excellently simple explanation of concepts of linear algebra and PCA. Applause for lector. I really liked this course and found it very useful for those newbies in machine learning like myself. I recommend this course to all my friends and others interested in.

Most challenging of all three courses but rewarding as well. Requires you have refreshed complex topics of Linear Algebra ( Khan academy and other you tube material are good starting point) . Looking forward to go even deeper in to this. Thanks Imperial !!!

I liked the course quite a bit. I found it quite challenging (I had never seen any PCA) but it always kept me very interested. I had to use several sources to read a little more about PCA and to complete the last exercises, the forum is very helpful.

Very good course, although the programming assignments are challenging and some background knowlege in linear algebra and vector calculus required. You will need to do some independent research at times. But the instructions are clear and concise.

This course is of excellent quality. The teachers captured the knowledge perfectly in the MOOC. Although if you do not have knowledge in Python, it will be very difficult to successfully complete the course. Thank you Professor and Staff Coursera

Excellent course - challenging yet rewarding with good feedback from the teaching staff.

The video and the transparent white board are also great - look forward to seeing more MOOCs from Imperial as well as the release of the upcoming book

Better than the previous two courses in the spec. by one aspect: additional helpful materials are clearly pointed-out. Thanks Marc Peter Deisenroth for your effort. The book of Marc Peter Deisenroth is also recommended. Great course.

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

This course is much more complicated than the previous two courses in the specialization. This one-of-a-kind course unravels the concepts and complex mathematics behind PCA. All in all, it was a pleasure to complete this course!

This is one of the best course, I have chance to follow on coursera. The lectures are very interactive, the labs and assignment are very relevant. Thanks for all the instructors for thice nice specialisation program ! Merci !

It is not an easy course I needed to see the videos more than 1 time to understand, and taking the 2 courses before is significant to cope with this course. I thank instructor Marc Peter Deisenroth for teaching this course.

This one is harder, I took longer time to figure out the assignments. Some of the concept that appeared in the assignments were not included in the lectures. I do hope that the assignments could have clearer instructions.

Very nice course. It will be great to have a course on Statistics for Machine learning covering advanced concepts in probability theory. Thank you for offering such a great course. I have learnt a lot and enjoyed fully.

Very good 3 courses for those of us who are beginners in Machine Learning and IA! However I miss a whole course, perhaps the first one of then four, teaching us what we need to know about python, numpy and plotting.

A great course. Learnt a lot, a lot of Linear Algebra, Projections/ Geometry/ all of these Mathematical ideas would help greatly in understanding of Machine Learning concepts and applying them to real world data!!..

It was a very nice experience with this course. I learnt a lot of Python Coding. The coding exercise was really good. It was tough for me to code in Python. But I took time for it. thanks to the faculty members.

Really nice course and kudos to the instructor. Week 4 was a bit challenging, but still he made it quite easy for us to understand. Very happy to have gone through this course and completed the specialisation.

I am not sure why the rating is so low for this course.

Personally, I found this course really insightful as the instructor explains what the different statistical measurements mean, and why are they useful.