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

4.5
5,798 个评分
985 条评论

课程概述

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....

热门审阅

OK
Jun 26, 2020

its actually a good course as it starts from fundamentals of visualization to the data visualization,the assignments this course provide are exciting and full of knowledge that you learn in course ..

RM
May 13, 2020

I am going for the specialization and I know this is just the second course in it and I haven't even seen the further courses yet, but this is already my most favourite course in the specialization.

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876 - Applied Plotting, Charting & Data Representation in Python 的 900 个评论(共 971 个)

创建者 Anant K

Aug 19, 2020

GOOD one

创建者 Tất T V

Oct 3, 2017

useful

创建者 SHAHUL E

Mar 2, 2018

heavy

创建者 NIKHIL C

Jun 6, 2021

nice

创建者 ERAGANABOINA S

Oct 31, 2020

good

创建者 MOHITH N

Jun 16, 2020

good

创建者 Eklavya J

Mar 21, 2020

na

创建者 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.

创建者 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.

创建者 Benny P

Oct 2, 2017

The video guide is pretty good, it shows you a lot of thing that you need to learn. It covers a lot of breadth and depth, but only briefly. For further info, and for the most part of your time when doing assignment, you need to seek the relevant manuals yourself. But that is fine, because matplotlib is very very rich library and there's no way all can be taught in a single course like this, and also it makes you familiar with how to find information yourself.

The main drawback is with the assignments though. I'm okay with the peer review system. The problem is that the assignment specification is not too clear. For example, in assignment 4, you need to think yourself about what you want to visualize. So a lot of time was spent on thinking about WHAT problem to display rather than HOW to address the problem (using plotting/visualization), which is the subject of this course.

创建者 Philipp A R

Mar 21, 2020

I liked the first course in this specialization more. As in the first one, the assignments require you to search StackOverflow, documentations and the discussion forums; videos are nice, but you won't learn a lot from them. Peer review is a double-edged sword. Some reviewers will give quite elaborate feedback, others do not put a lot of effort into their reviews. Peer-reviewing others can be quite annoying as often you have to wait several hours for submissions of other learners. Not to mention the quite large amount of learners who hand in plagiarized code (please look out for these cases if you participate in this course).

创建者 Tiberiu T

Mar 31, 2018

This is a whirlwind course that glibly covers some very important concepts without devoting enough time to each one. Week One, although important, should be replaced with more coverage of matplotlib, or a review of the different types of charts and when to use them.

Also, although I appreciate the in-video quizzes, it is difficult to go back and review the concepts you learn from them because they are not in the Jupyter notebook. For instance, there was a method Dr. Brooks used in a solution to an in-video quiz and I could not remember where I had seen it. I stumbled on it again after reviewing the video for something else.

创建者 brian a

Apr 2, 2017

The first course in this series was really good and this one was so-so at best. I got some skills out of it since I obsessively plotted everything and over did the assignments, but the peer grading rubrics are crap. It's all or nothing so if you submit *anything*, you get a grade (and it usually approaches 100%) but I didn't really get much helpful/thoughtful feedback on anything I did since you literally get ZERO feedback from the instructors (nothing!) nor did I get much in the way of helpful info from the people who peer reviewed my work. I find that pretty disappointing really.

创建者 Oliverio J S J

Jan 21, 2018

The contents of this course are interesting from the point of view of software engineering, but I am not sure if data scientist need such deep knowledge of graphic libraries. The main problem with the course is that the assignments require much more time than the one indicated in the course planning. In addition, assignment descriptions are often confusing, open to interpretation, and lack enough level of detail, which forces the students to begin by investigating what they have been asked to do.

创建者 Jaime R

Jun 23, 2021

V​isualization in Python is still a bit of a chaotic mess, with so many different interfaces to matplotlib, one is left a bit confused, and its a bit hard to become a power user. Was hoping this course would provide a solid foundatation. Not sure I'm any more of a power user after this course. I'm still left to googling and looking at package code base to decipher how to best leverage. All this eats time, time not being spent doing analysis which should be ones focus.

创建者 Bhavin P

Dec 3, 2018

This course introduces the learner to the various design principles that need to be followed while creating effective visualisations that include Alberto Cairo and Edward Tufte's work. It explains the information-visualisation wheel and proceeds to explain how to create visualisations in python using the Matplotlib Library. Various kinds of plots such as Line Charts, Bar Charts, Histograms, Scatter Charts are covered. Seaborn is introduced as additional library.

创建者 Sarah B

Oct 15, 2018

This course gives an overview of plotting capabilities but I think it could have been presented more methodically. I think the challenge is that there are many ways to generate plots and so this is more a survey of those capabilities. I now know enough to go to stack overflow and matplotlib documentation and figure out what I need to get done, so my goal is accomplished, but my understanding of the plumbing of the different commands feels a big hazy.

创建者 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.

创建者 Jonathan V C

Dec 17, 2019

All material, explanations and content are great, no complains there, but I insist with the peer-graded assignments, we don't know if we are being graded well and some people just don't care, take points off for no reason associated with the rubric. Also, I like when the data source is given, I don't have time to search for a source of information that fits my investigation or the imposed topic of the last assignment.

创建者 Peihong H

Dec 25, 2017

First, I would prefer there is a way to download the sample code professor Brooks used in the course. The screen showing his code moved too fast, and I have to pause and typed to try them out. Second, I will suggest the course show more code examples, more explanation for matplotlib architecture rather than most of the time just verbal description from the profession

创建者 Renier B

Sep 19, 2017

The course is okey - lots of fuzzy theory such as Cairo's principles. Interesting stuff, but also quite self explanatory and seemed like a waste of time.

I would say its worth it to do this course if you have not had any exposure to Matplotlib or seaborn, but if you've done any significant using those then this course will feel a bit underwhelming.

创建者 Venkatesh P

Mar 24, 2021

The python course followed a reinforcement approach with multiple examples and practice problems after every video. I liked the assignments in this course very much. They are very challenging. However the course isn't very informative. It will be helpful if the course is modified in a similar style to Python courses.

创建者 Varun D P

May 6, 2018

Lot of working is required from our side. Not at all an introductory course! More like advanced level course. Requires lot of time, we have to find the documentation ourselves and ask question on stackoverflow. If you are looking for introductory course like Dr. Chucks courses I suggest not to take this course.

创建者 Christopher I

Dec 22, 2017

This course is really as good or as bad as you make it for yourself, since it is quite bare, more a sort scaffold for you to do your own learning and projects. This is arguably the best way to learn though, which is why I like it. But, it may be challenging for beginners to get the most out of it.

创建者 Khokon C S

Jul 17, 2020

I think length of the tutorial should have been a little bit longer for extensive discussion. The professor should have used words which are most of the cases self-explained or easily understandable from the perspective of audience, so those were somewhat tougher to catch up with professor.