Some exercises of the assignments where ways to difficult compared to what learned during lectures: much more details should be provided about data manipulation

the course is really good but there are issues with autograder. Though they are addressed in forums you'll have to go through them and hence wasting your time.

You'll spend more time struggling with the jupyter notebook (assignment platform) than actually writing or learning code. The lectures are really good, though.

Great content. But some assignment questions are not that clear and might cost you more time than its worth. And feedback from mentor is not that responsive.

The course is well designed and assignments are complex. What I did not like about this course is that the assignments are not well explained with examples.

The main problem is with the auto grader. There are too many issues making it cumbersome to get the assignment submission right in one go. Please fix this.

Had to learn most of it by myself. Got discouraging at a certain point. Should have informed about the prerequisites.

Learn Numpy, Pandas before enrolling.

Some parts were quickly rushed through and poorly explained. However, they did explain the bare bones of pandas, which was the main reason for this course.

There is one critical technical problem lying in the assignment three and already caused hundreds of students' grade blank in the forum, including myself.

As a beginner I found it a bit of a brisk over the topic. There was a lack of basic questions. But in the end I was coping up and then the course ended.

too fast in explaining it was bit difficult to keep up with the explanation,small code example were taught but assignments questions was too difficult

Great course material, but the autograder system was frustrating to work with for assignments, and often made me less motivated to work on the course.

The course is okay for beginners as it is having only few lecturers for basics. Coursera experience was good. Overall i am satisfied with the course.

The assignments are not even close what is being taught. We are taking this course so we get everything in one place. Curriculum has to be improved

I​ think the lecture about grouping could be improved with more practical examples, I had to search for external sources to understand the concept.

Not at all for beginnners. Fast-paced with more focus on self-learning and grinding,rather than focussing more upon the concepts. Dry presentation.

Quite bad knowledge delivery from lectures. The course is rather self learning than course. A lot of vague points and uncertainties in assignments.

The course instructor could have been more elaborate with the examples. I felt there was a wide gap between the exercises and the course material.

Assignments are challenging, but some questions are very vague and require lots of trial and error guesswork to get the autograder to accept them.

Assignments are great to reinforce your learning. But the instructor does not cover many topics and leave you with a lot of questions unanswered.

Please update the auto-grader such that is it compatible with current version of Jupyter notebook, very frustrating dealing compatibility issues

This course is a nicely organized. However assignments are not completely clear. Especially assignment 4 needs more explanation and details.

Subject matter was very good. Some of the assignments were not clear on instruction, and some of the Coursera functions were buggy or broken

Material delivered a bit too rapidly to effectively assimilate. Often, further external research is needed to find solutions to assignments.

I don't think this is a good enough course to "teach" you "data-science". All this does is give you an overview of things you need to know.