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學生對 密歇根大学 提供的 Applied Plotting, Charting & Data Representation in Python 的評價和反饋

4.5
3,472 個評分
570 個審閱

課程概述

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. The third week will be a tutorial of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data. This course should be taken after Introduction to Data Science in Python and before the remainder of the Applied Data Science with Python courses: Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python....

熱門審閱

SB

Nov 03, 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

A

Mar 06, 2018

Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.

篩選依據:

526 - Applied Plotting, Charting & Data Representation in Python 的 550 個評論(共 557 個)

創建者 Vladimir I

Aug 23, 2017

Overall, it is a reasonably good course. Content touches not only how to 'program' a simple / interactive / animated visual but also some theoretic aspects of plotting in general. An interesting thing about this course is that you will decide how challenging the submissions will be though this will not affect your grades. My final assignment for this course: https://github.com/vdyashin/EarthquakesInAsia. In this course, I learned how to create an interactive plot and applied this knowledge in order to create a portfolio-ready visualization.

Though, since this course is about plotting and charting there is a lack of visual materials and great examples of use cases. For potential Russian-speaking listeners, I would recommend sticking with the MIPT-Yandex specialization instead of this one. If that specialization would seem too hard then finish this specialization first. Though, they both specified as an intermediate level. I would claim that this one is for beginners.

創建者 VenusW

Mar 31, 2017

First of all, the instructor is very responsible, keep updating information on the forum and course material. The course is a decent level of basic plotting technique review, should be in more detail. Compared with the first course of this specialization, this second course is much less challenging, require less effort to accomplish. The first course is the one attract me of this specialization, the second one, somehow, is a bit disappointing, especially compared with plotting skill of R in another data science specialization, which is even an elementary level course. This course cannot be labeled as intermediate level.

Another problem with this course is the peer review, the grading policy should be changed to punish irresponsible reviewers, no useful feedback got. What kind of responsible one provide feedback in two words, where require to answer three questions (week 4 assignment) to review.

創建者 Leon V

Apr 04, 2017

Seemed more introductory, here are the tools - go have fun rather than actually teaching teaching

創建者 Peter B B

Feb 10, 2018

Fine for learning matplotlib, little additional benefit

創建者 Xiao Y

Apr 03, 2018

The coding assignments are much harder than the content taught in the course. Need to do a lot of self-learning and searching. I personally don't prefer this style

創建者 John W

Mar 20, 2018

Solid, but not as good as Applied Machine Learning.

創建者 Sylvain D

Mar 19, 2018

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

創建者 Sakis N

Nov 13, 2017

Excellent lectures. I believe the assignments should have been more specific to make students combine both lessons(1 & 2 ) so as to use all knowledge they acquired.

創建者 am

Apr 14, 2017

The last week assignment is easier and no strict rules to achieve. The majority will do the minimum to finish the course.

It would be more efficient to push all students to make hard plots in Matplotlib (interactive + animation) with strict rules.

This is not a level of an intermediate course!

創建者 Khoa N

Jul 03, 2018

The course goes really fast, and I think the tutorials on Matplotlib are really brief and should only be seen as an introduction to what we can do with it. In order to use Matplotlib effectively, we have to learn a lot from other sources.

創建者 Avi S

Jun 29, 2018

tough unexplained assignments

創建者 Rodolfo G

Jun 21, 2019

it is not as extensive as other courses in Coursera, it should try to expand a little more its content

創建者 Harshith S

Jun 03, 2019

Better than the previous one. But still very vague explanations

創建者 Marcel K

May 21, 2019

I wish they'd update the accompanying notebooks - their versions of pandas and related libraries are several years behind at this point.

創建者 Saman H A

Aug 15, 2019

Materials, slides and videos were not adequate and didn't provide enough details.

There were many many typos and misleading syntax errors in lecture subtitles.

創建者 Andy F

Sep 20, 2019

The lectures really need to flesh things out more, they too often feel too fleeting and leave more than they probably should to searching other resources. Questions for the final piece clearly haven't changed in at least two years and lack clarity as to what should be done

創建者 Sandeep S

Sep 20, 2019

Week 4 - Assignment is very frustrating.

創建者 Alex W

Oct 26, 2019

The instructions for the second assignment are terrible. My peers graded my assignment based on what they thought the instructions implied I should have done instead of what it explicitly stated so I may have to repeat the assignment and could risk not passing the course which puts my whole specialization at risk. It's ridiculous since I spent sooooo much time on the assignment already due to lack of guidance from the video lectures.

創建者 Muhammad s k

Oct 12, 2019

Not a defining one

創建者 Jason B

Oct 16, 2017

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.

創建者 Linda L

Jun 13, 2018

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

創建者 Filippo R

Mar 30, 2018

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.

創建者 Kumar I

May 25, 2017

Compared to the first course in this series, I found this one not so challenging. The final project was very loose (I understand that the instructors wanted to give the feel of a real research). The first assignment was very superficial. As much as Cairo's principles are important, I feel devoting an entire assignment to that is justified. The second and third were relatively straight-forward, but that was perhaps the saving grace.

Wish the course spent time in dwelling on complex visualizations.

創建者 Xing W

Jul 25, 2017

Not well organized.

創建者 Steven O

Mar 18, 2017

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