While it clarified a lot of things, some parts were not well explained. If I didn't have STEM background and it wasn't a refresher for me I would struggle.

To be honest the videos are too plain and boring too watch I think the videos should be more enjoyable and give a more understandable examples

Gives a very good understanding right uptil week 4, but then Eigenvalues and Eigenbasis could be better explained.

Very basic fundamentals could have done more. But overall a good course to gain insight into the topic

eigen vector and eigen values part is not explained briefly other than that course is just amazing.

Very basic, some interesting topics are omitted. But visualizations are good.

Eigen Values and Eigen Vectors wasn't explained in great details

the grading criteria is not accurate, slides are not so clear

Fast Explanation.Suit for Native English Speakers.

too easy

I had to fix so many issues with indentation, a broken jupyter notebook, broken test files. Don't waste your time. And to force people into PAYING for a certification earned DURING A & DAY TRIAL is just shitty man. Seriously, go to hell. Why would I pay for a course that constantly broke, and spent 3 hours fixing? That's so beyond greedy and money ahead of education that it isn't even funny. Assholes.

This course was not helpful to me. I didn't really understand what I was achieving in the last lab and although I passed all the quizzes, I found myself going to external resources constantly for answers. It's this weird mix of overly simplified metaphors and then slides that truncate the mathematical steps they show which left me at least having to pause it and figure out what happened. IDK.

The videos end abruptly. The trainer speaks very fast and the topics don't seem to follow sequence. For example, they introduce basis before getting into the detail and left me confused. This is a low bar compared to the Machine Learning Specialization

The intuition (for ML & DS) was not established; the explanations were often thin; maybe drop the "for ML and DS" part off the description?

Not possible without knowing Python 3 already. Also doesn't really talk about ML so I don't know how any of this is applicable to ML.

Los laboratorios de python son complejos para una persona que recien empeza a programar, un ejemplo de eso se ve en la tara C1W2

This course is kind of unstructured and the assignments and quizzes contain lots of uncovered content.

Material is not complete explaint. There are not Hins in Labs.

eigenvalues and vectors were poorly explained

alot of issue faces in assigments submission

Too confusing

NO

Completed all the way up through the last assignment in week 3 with 100% on all assignments and quizzes. Completed all but the very last question in the programming assignment with matching "Expected Output" and "All Tests Passed" , and pasted the "#grade-up-to-here into the cell second to last cell. I have submitted many times, receiving anywhere from 0-50%. Have emailed support, and never even received a generic response that it was received. Very frustrated and tempted to leave Coursera forever. :(

this course is not well structured for beginners, it is not taught well with details. the instructor goes over the concepts in short manner, then quiz you and also quiz you in python numpy library, the order of topics is not correct in my opinion

Graded quizes have questions that do not explain what format the answers should be in. ZERO support from Coursera when needed. So disappointed with this course thus far. Hopefully, it gets better as I go on.