The assignments kill this course, great instructors, and pace, in my opinion. (I am a beginner in linear algebra and I understood the concepts without needing Google or external resources)

I think the course is more suitable for those who have had comprehensive theoretical knowledge in linear algebra and intend to learn more about its practical use and its relevance to code.

The course is good. But the last module (week) is not so good. I think that the explanation of the Page Rank algorithm is not very good. I also think that the final test is very confuse.

Overall course was good, I have learnt few new concepts which I haven't know till now. But at the end, things were not clear while putting all together for solving page rank algorithm.

Linear Algebra content is great, however, was not aware that a huge portion of grade is based on Python programming exercises!!! Only need to learn Linear Algebra, not programming!!!

Intuitive geometrical representations of eigenvalues and eigenvectors in 3blue1brown style. Had some concerns with a few theoretical inaccuracies of the material presented.

It was a good to review linear algebra again and see how what I learned in my first year course at university could be applied here! Plus it was good to see Python again.

The course feels very disorganized in general. Some quizzes are about 10 standard deviations from the average difficulty, which is befuddling to say the least.

It is good course for machine learning. But I didn't fully understand the page rank system with damping.

More explanation of damping is needed for the newbie.

Transition from explanation of basic to advanced concepts could have been better. There was an assumption that few things was already know to the learner.

Not enough focus on how material connects to machine learning. A case study example would help, as would a very slow, detailed step-by-step illustration.

Nice one. But realized I needed more foundation on this matter. So decided to abandon and level up my topic knowledge in Khan Acadamy. I will be back.

Good for someone who has bit background in Linear Algebra and Python. I won't recommend this work for a completely newbie as this course lacks depth.

I think this course is a little bit hard for a beginner with python. And I hope that the teacher can talk more about the Machine learning part.

Very good explanations on difficult subjects but a bit short coverage of various cases, thus some assignments and quizzes were challenging.

Answers to Several questions in Week 5 quiz around eigen values and eigen vectors need to be revisited as they donot appear to be correct.

This course consists of very fundamentals of linear algebra. I expected advanced linear algebra contents and more software applications.

The course gives a good beginner-friendly Introduction to Linear Algebra. But the courses could cover a little more topics in LA.

I would give it 3.7, examples are good but the vectors the lecturer draw were no easy to understand because of drawing by hand.

TEverything is good until you reach the coding assignement. Then it is a complete disconnect with no resources available.

The Eigen system could have been better explained. The last quiz was too hard and the concepts required were not covered

Lot of the concepts seemed glossed over and could have used more guided practice and/or linkages to real world problems.

It is so complex and contains so much knowledge but hard to understand for beginner or intermediate in mathematic

The instructor is skipping a lot of material and the quizzes require working with external sources to be solved.

This course would be perfect if more elaboration on the maths required to complete the quizzes, was provided.