Learner Reviews & Feedback for Mathematics for Machine Learning: PCA by Imperial College London

Course is inconsiderate to new learners in that new concepts were very sloppily introduced. Like the first two courses of the specialization, this course is shallow, shouldn't be anyone's introduction to the subject and is a refresher at best. Unlike the other two courses, it assumes python knowledge, doesn't explain relevant syntax in the assignments; which made me take a lot of long unnecessary detours to get the python implementation right.

After the other two awesome courses of the specialization this one stays far behind my expectations. Weakest course of the specialization. Instructor is obviously knowledgeable but does not provide much intuition. Programming assignments are really difficult and at many points frustrating. 2 more weeks and therefore comprehensive instructions would be desirable. Couldn't appreciate that course as much as I wanted to.

After having done the first two parts of the specialization, I am afraid this one didn't stand up to the high quality bar the previous two had set. The programming assignments are unnecessarily long and complex and the overall material is not as engaging, connected and concise. I might give it a good rating as a standalone but now I can't avoid comparing it to the other two parts of the specialization.

This course is a great departure from the premise of bringing Mathematics and ML together. The instructor basically throws dozens of calculations, Math for the sake of Math. No intuition is gained, either. The instructor is only preoccupied with writing down the calculations. You either "swallow" all the Algebra or not. I'd suggest the complete reformulation of the videos.

Compared to the first modules in this series, the instructor explains almost none of the intuitions behind the maths and will skip over large essential pieces required to complete assignments and quizzes. It assumes a wide knowledge of programming and broader maths that was handled significantly better in the earlier courses.

The explanation of the course is hard to understand. Some misunderstanding. I have to study on youtube or somewhere to pass this course. The videos in the course are lack information. 2 stars because of the PCA assignment helping 1 plus star for the course. The two courses previous in this specialization are good.

This is the least effective course among the three courses in this specialization. The reading materials have no context. People who have not been around those math symbols have no idea what the reading materials mean. They are not intuitive at all. The design of the assignments are poor as well.

This course has been a nightmare. Dense and obscure lectures, "challenging" assignments asking for things that haven't been properly taught in the lectures and often unclear instructions.

Yes, some useful concepts are taught but overall it's rather a waste of time.

Programming assignments seemed to be written from a completely different direction, and instructions are vague and misleading. (The math assignments were not so bad.) There was no staff or mrntor engagement in the forums during the period of the course.

Unlike the prior courses in the series, topics not clearly explained and brought too sudden. Also none of calculations shown completely, instructor just wrote results in the end. Due to all these reason I was not able to finish the course.

The course assignments could be improved dramatically, though the course itself has very good content if you want to have a taste of how linear algebra (predominantly) can be implemented to solve machine learning problems.

First two courses in this series are great but not this one. Lectures and exercises are not related. I do not feel like I have totally understood PCA. Was able to complete the final assignment thanks to the internet.

The course is awful, it's nothing compare to previous 2 courses. It has a lot of errors in assignments objectives and quizzes! The explanation is complete crap! I'm wondering how was it even allowed on Coursera?!

The theory is well explained and the level of complexity is very similar to a University course, but the assignment environment is buggy and the assignments are poorly designed and very frustrating.

Needs to demo a little bit of code owing to the complexity of the course content.Lectures gives just a high level understanding only. Assignments are taking far more complicated than expected.

Even though the videos and quizzes are well produced and informative, the assignments are so poorly designed that they can only bring about some frustration with the learning process.

Faced a lot of problems in exercises. Don't feel that i have completely understood the concepts. This course can be made more learner friendly with better explanations.

Explaination of many things are skipped, assumption was made by the instructor that lot of things were already known by the learner. It could have been much better.

The difficulty of the course is inadequate and the pace is not balanced. Requires a lot of search for additional resources to understand materials. I cancelled.

After first two amazing courses in this specialisation, third course was a huge let down. One skill I learnt from this last course is patience.

Lack of examples to clarify abstract concepts. Big contrast in quality compared to the other courses in this specialization.

Poor explanation by the instructor. Previous ones were very helpful. I didn't understand many topics well

Everything is okay but there is a huge drawback with the programming explanation part.

very wired assignment, a lot of error in template code. The concept is not clear.

The lectures were not clear. I had to use other sources to understand lectures.