学生对 密歇根大学 提供的 Applied Plotting, Charting & Data Representation in Python 的评价和反馈

Fine for learning matplotlib, little additional benefit

Good but I feel not comfortable with peer reviewing...

Not so good as the first course of the specialization

Solid, but not as good as Applied Machine Learning.

Overall a good course, but has to improve.

Week 4 - Assignment is very frustrating.

limited theory on the subject

tough unexplained assignments

Peer grading is not worthy

Little hard to understand

Skills taught is limited.

This was a hard one.

Not a defining one

Good course.

best I think

sucks

Programming can be a slog when the right materials are not available or the documentation is sparse. It is for this reason that I choose to take and pay for a course instead of muddling around the documentation alone and pulling my hair out. This course does not remedy that issue. I find the professor likeable and he cares about his subject but I have to say it directly and bluntly: the videos are examples of teaching issues with incomplete treatment of basics before moving onto complexities. There is more than a little word salad to get through in the videos which are more and more frustrating as you re-watch them expecting you might have missed important info needed to complete the assignments. It is frequently the case that you have to dedicate far more time to background research in order to complete exercises than the time commitments quoted here. This course could be so much better with some rethinking on how to emphasise and present key concepts so that we are enabled to start from a solid base instead of wandering half-lost as soon as we begin coding. Maybe a collab with professor Severance could remedy.

Some of the material was interesting but on a whole not nearly as engaging as course 1. I fully can appreciate how the principles of chart design are valuable to the subject matter covered in this series but on a whole I would have liked more focus on the technical skills and maybe had the academic perspective on design extra reading.

Also the peer grading portion of this course is a little rough. The people that graded my work were great but I don't expect them to engage my work in a very meaningful way. It's not realistic to ask them to give their full effort to grade 3 assignments for an online course that they pay for. My personal preference would have been to structure the assignments so that they could be automatically graded like in course 1.

The concept is good: introduce the theory of information visualization and introduce how to make charts with Python and matplotlib. Unfortunately the materials are deficient for the programming part. There aren't nearly enough practice exercises to help you learn matplotlib. The previous course in this specialization (intro to data science in python) by comparison has many more guided practice exercises, and I am disappointed that this course does not live up to the standard set by the first course. If you are taking the complete specialization, as I am, then I guess it's worth it and I hope the next courses in the series have more material.

From the previous course I know what was coming.

And it was tuffer than Tufte...

I'm not that confident with the structure of the course. I would prefer more mini tests on checking the knowledge of the singe plotting commands and then heading to the assignment of each week.

I think that the challenge would be less frustrating when beeing more skilled with the tools in your plotting toolbox.

The rate lectures/assignment is disappointingly low, a lot of time goes only to find data available online and to find questions to answer. In my work I have plenty of opportunity to apply data science and very little knowledge on how to. This course gave me more assignments and not so much tools.

This course only scratches the service of the subject and asks the learner to learn almost everything by himself searching the Internet. The lecture content must be expanded significantly in order to give enough knowledge for the programming assignments.

Peer-grading is horrible. Nobody reads assignments or checks your work - they just give top grade for every category and leave "." as a comment, all to breeze through the mandatory peer grading. This certificate has very low value.

I think there there is too much time given to the esoteric of what makes plots pretty rather than the nuts and bolts of how to do it and the limitations of using Pandas and Matplotlib for real world data

I am not too crazy over the peer review assignments plus the course was hard to follow