This is one hell of an inspiring course that demystified the difficult concepts and math behind PCA. Excellent instructors in imparting the these knowledge with easy-to-understand illustrations.
Relatively tougher than previous two courses in the specialization. I'd suggest giving more time and being patient in pursuit of completing this course and understanding the concepts involved.
By Dr. N D•
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.
By AKSHAT M•
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.
By Krishna K M•
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.
By Akshat S•
I will present my self with some amazing songs!!
Excellent staircase to the heaven for learning PCA.
Breaking the habit of struggling with hardcore bookish mathematics.
Loose yourself in this adventure!!
By Jose A•
Well explained, some issues with assignments but some of them are to not just type and think a little.
May be one is a real mistake... hard time with it, but lot of learning too.
By prudgin g•
Challenging, but doable. Has some bugs in coding assignments, but clearing them out makes you understand things better. Get ready to spend extra time understanding the concepts.
By Christian H•
This course is well worth the time. I have a better understanding of one of the most foundational and biologically plausible machine learning algorithms used today! Love it.
By Tse-Yu L•
Practices and quiz are designed well while I will suggest to put more hints on programming parts, e.g., PCA. Overall, this series of course are pretty useful for beginner.
By Miguel A Q H•
This is the best course of the specialization, its very hard but it lets you to understand very important concepts of what means dimensionality reduccion.
By Aymeric N•
This course demystifies the Principal Components Analysis through practical implementation. It gives me solid foundations for learning further data science techniques.
By XL T•
It is a bit difficult and jumpy. You will need some hard work to fill in the missing links of knowledge which not explicite on the lectrue. Overall, great experience.
By Fabrizio B•
Definitely the most challenging of the course making up this specialization. Finishing it with full scores is proportionally far more satisfying!!! Well done Marc!
By S J•
Your Teaching and Video quality is par excellence.....Thanks a lot for such amazing stuff...I am looking forward to joining more courses in the same line
By Christine D•
I found this course really excellent. Very clear explanations with very hepful illustrations.
I was looking for course on PCA, thank you for this one
By Ananta M•
Although the course was little out there and the instructor was trying his best to articulate a difficult topic, the overall experience is great.
By Prime S•
Nicely explained. Could be further improved by adding some noted or sources of derivation of some expressions, like references to matrix calculus
By xiaoou w•
great content however the programming part is too challenging for people without propre guidance in the subject. the videos aren't of much help.
By J A M•
Solid conceptual explanations of PCA make this course stand out. The thorough review of this content is a must for any serious data researcher.
By Amar n•
Just Brilliant!!! Very well structured with very clear assignments. Doing the assignments is a must if you want to get clarity on the subject.
By Sateesh K•
This course should be part of "gems of coursera". Excellent specialization, thoroughly enjoyed it. For me the 3rd course on PCA was the best.
By Moez B•
Excellent course. The fourth week material is the hardest for folks not comfortable with linear algebra and vectorization in numpy and scipy.
By Hasan A•
What a great opportunity this course offers to learn from the best in this simplified manner. Thank you Coursera and Imperial College London!
By Duy P•
Excellent explanation from the professor!! Besides he is the author of the book Mathematics for Machine Learning. You should check it out.
By Alexander H•
Highly informative course! Loved the depth of the material. Found this course content highly useful in my current project based on PCA.
By Prabal G•
great course for mathematics and machine learning...A big thanks to my faculty to guide like a god in this applied mathematics course